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Location: Metn, Lebanon The Company Toters is an on-demand e-commerce and delivery platform and operates a service that enables customers to get anything in their city at the highest level of convenience. At Toters, technology is at the heart of everything we do. We have product teams that are working hard every day to create products that make our customers' lives easier. Our engineers are also continuously creating solutions to make our processes more efficient, all in an effort to get to our customers fast and at the best cost. If you are interested in working in a high growth startup environment, and look to be part of a team that will potentially change the way customers shop in the Middle East, apply now. Role We are looking for a Senior Data Analyst to own end-to-end analytics for our core engines. In this role, you won't just build dashboards, you will partner directly with Business Leaders to define roadmaps, business cases, and design synthetic experiments. You will turn ambiguous data into an actionable strategy that directly impacts customer conversion, driver efficiency, and growth. What You’ll Do Product Partnership & Strategy: Collaborate with Product Managers, Strategy Directors and Business leaders to translate complex business problems into data-driven product features and strategic roadmaps. Experimentation & A/B Testing: Design, implement, and analyze rigorous A/B and multivariate tests to evaluate feature launches, pricing mechanics, and UX changes across our apps. Funnel & Marketplace Optimization: Deep-dive into consumer retention, funnel conversion, courier dispatch dynamics, and merchant metrics to unlock business growth and improve unit economics. Metric Standardization: Define core product KPIs and maintain a single source of truth by building robust data models (data warehouse) and production-grade dashboards (Tableau). Data Quality & Infrastructure: Enforce strict data validation standards, maintain data governance across clickstream/event tracking, and ensure downstream reporting reliability. Technical Leadership: Mentor junior analysts, lead code reviews for analytical SQL scripts, and elevate overall analytics best practices across the team. What We’re Looking For Experience: 4+ years of data analytics experience, ideally in a product-led tech company, hyper-growth startup, or multi-sided marketplace (e.g., delivery, ride-hailing, e-commerce). Advanced SQL Mastery: Recognized expert in writing clean, modular, scalable SQL code optimized for complex datasets. Statistical Rigor & Python/R: Strong understanding of hypothesis testing, causal inference, and statistical modeling using Python or R. BI & Data Modeling: Hands-on experience building centralized dashboards in Tableau and working with modern data stack tools (dbt, Snowflake, BigQuery, Databricks). Product Intuition: Demonstrated track record of leveraging user behavior analytics (event tracking, cohort analysis, funnel drop-off) to directly influence product decisions. Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or an equivalent quantitative field. Nice to Have Experience working with clickstream tools (Mixpanel, Amplitude, Segment). Hands-on knowledge of data engineering tools or orchestration frameworks (Airflow, dbt). Experience in experimentation tools (Statsig)

Location: Mississauga Workplace: hybrid At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.   With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.    At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.   Join us in redefining healthcare — so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.     **Travel to Office expectations** For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.   For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role. Team Summary This team will serve as the product owner for the machine learning platform capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support traditional machine learning (ML) and hybrid ML/LLMsolutions. This centralized team with deep specialization will closely integrate with key horizontal partners to ensure delivery of safe, scalable, and high-impact AI products. Job Summary The Senior Machine Learning Systems Engineer will work closely with the Product and Engineering teams to design, build, and operate the machine learning platform that enables teams across PointClickCare to develop, deploy, and scale ML solutions. The Senior AI Machine Learning Systems Engineer will also build and maintain the pipelines, tooling and infrastructure for model training, deployment, serving, and monitoring that underpin our AI products. Key Responsibilities   Collaborate with product and engineering teams to translate ML needs into reliable, reusable platform capabilities. Design and build scalable data and ML pipelines that support model training, evaluation, deployment, and serving. Develop and maintain ML Ops tooling and workflows, including CI/CD for models, model registry, feature stores, and experiment tracking. Ensure the reliability, observability, and performance of ML systems in production through monitoring, alerting, and automated remediation. Implement comprehensive security mechanisms for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring. Securely integrate the platform with existing systems, APIs, and data sources with secure communication protocols, and optimize infrastructure for cost, performance, and scale. Mentor engineers on the teams and promote reusable platform patterns and best practices.   Qualifications & Skills   Expert level in Python and Java, and strong software engineering fundamentals. Experience designing and building ML platforms and MLOps workflows, with familiarity with tools such as MLflow, Kubeflow, Ray, and model-serving frameworks. Experience with cloud platforms (Primarily Azure, secondarily AWS and GCP) Experience with ML runtime containerization, optimization, and orchestration (Docker, Kubernetes).   Preferred   Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field. Working familiarity with Azure Machine Learning components and Databricks processing and serverless environments Experience implementing security at scale including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring. Experience optimizing large model training and inference (including LLM serving) for performance and cost. #LI-AV1 #LI-Hybrid PointClickCare Benefits & Perks:   Benefits starting from Day 1! Retirement Plan Matching Flexible Paid Time Off Wellness Support Programs and Resources Parental & Caregiver Leaves Fertility & Adoption Support Continuous Development Support Program Employee Assistance Program Allyship and Inclusion Communities Employee Recognition … and more!   It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.   When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it.  If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com    PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information. At PointClickCare, base salary is one of the many components that make up our total rewards package. The CAD base salary range for this position is $174,000-$218, 000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role

Databricks, an American IT firm specializing in a unified cloud platform for big data and AI, is seeking Forward Deployed Engineers in Amsterdam and Senior Forward Deployed Engineers in Stockholm. Candidates should have experience with Python, Scala, JavaScript or TypeScript, Apache Spark, and cloud platforms such as AWS, Azure, or GCP. Familiarity with CI/CD pipelines, MLOps, machine learning and AI models, as well as AI APIs, is required. These positions are on-site roles.

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: We are seeking a Senior Director to lead our Enterprise Reporting and Analytics Engineering organization, a team of analytics engineers, report developers, visualization specialists, and people leaders. This organization focuses on the last mile of the enterprise data supply chain: the semantic models, curated data products, metric definitions, and consumption experiences that turn engineered data into decisions. This is not a traditional reporting leadership role; the classic notion of “reporting” in the form of a myriad of dashboards and filters is racing towards obsolescence. But the need for data and insights, and the need to deliver it in a way that is digestible and actionable, is timeless. Yes, governed dashboards and trusted reporting remain the foundation, and this leader must be excellent at that foundation. But the mandate is to move the organization decisively beyond static reporting toward a proactive, intelligent analytics capability: partnering with Data Science to productize and visualize their models, enabling generative AI and LLM-based access to our data, building exception-based systems that alert users when outcomes deviate from expectation in a statistically meaningful way, and designing agents that monitor data continuously and deliver insight without being asked. Analytics engineering shares much of its DNA with data engineering — modeling, transformation, testing, version control, CI/CD, performance and cost discipline — but is oriented toward business enablement rather than platform and pipeline. Success in this role therefore depends as much on partnership as on technical depth. This leader will work shoulder to shoulder with Data Engineering on the boundary between platform and consumption, with Product Management on roadmap and requirements, with Data Science on advanced analytic products, and with Analytics Operations on a disciplined intake and prioritization process that makes the best possible use of finite capacity. The ideal candidate has spent years building the traditional foundations — governance, metadata, lineage, dimensional modeling, engaging with enterprise BI platforms— and is now looking to apply that rigor to a fundamentally different generation of analytic products in new and innovative ways. What you'll be doing: Organizational Leadership Lead, coach, and develop an organization of approximately 30 people, including managing through frontline managers; own hiring, role clarity, career pathing, performance management, and succession planning. Define a multi-year vision and roadmap for enterprise reporting and analytics engineering, and translate it into quarterly outcomes the team and its partners can measure. Partner closely with Product Management to jointly shape the multi-year enterprise end-to-end data strategy. Own the organization's budget, vendor relationships, and contractor or offshore capacity. Establish and sustain an engineering culture within an analytics function: peer review, automated testing, documentation standards, source control, CI/CD, etc. Analytics Engineering and Data Architecture Drive maturity of the last-mile architecture in partnership with Data Engineering: curated marts, semantic layers, reusable data products, and certified datasets that serve reporting, ai enablement, data science, and downstream applications. Define and enforce dimensional modeling standards, transformation frameworks, and modular, tested, version-controlled analytics code. Own the enterprise metric layer so that key business measures carry a single, governed definition regardless of where they are consumed. Partner with Data Engineering to define clear contracts and handoffs between pipeline and platform work and last-mile modeling, including shared tooling, standards, and escalation paths. Manage query performance, warehouse consumption, and platform cost as first-class engineering concerns. Data Governance, Metadata, and Lineage Own cataloging, business glossary, data certification, and stewardship workflows, leveraging tools such as Atlan as the primary metadata platform. Maintain column-level lineage across the analytics estate to support impact analysis, change management, audit, and root-cause investigation. Leverage data access provisioning and entitlement models, including row- and column-level security, in partnership with Security, Privacy, and Compliance. Collaborate with Data Engineering to drive data quality monitoring, freshness and availability SLAs, observability, and incident response for analytic assets. Enterprise Reporting and Data Visualization Drive analytics engagement by leveraging enterprise visualization and provisioning platforms, including Domo and Tableau, in partnership with Data Engineering. Ensure best practices are followed in data architecture, governance, adoption, performance, and total cost management. Set visualization and information design standards that make reports readable, consistent, accessible, and decision-oriented. Rationalize the existing reporting portfolio: retire redundant and unused assets, consolidate overlapping content, drive down tech debt and drive consumption toward certified sources. Build a durable self-service capability through training, templates, community, office hours, and clear guardrails on what belongs in self-service versus centrally managed content. Advanced, Proactive, and AI-Enabled Analytics Partner with Data Science to productize their work: build the visualization, interaction, monitoring, and feedback loops that turn models and research into products the business actually uses. Partner with Product Management and Data Engineering to enable generative AI and LLM access to enterprise data. This includes preparing the semantic and metadata foundation that makes data legible to models, delivering conversational analytics, text-to-SQL, and retrieval-augmented experiences on governed sources, and establishing guardrails, evaluation, and accuracy monitoring so that answers can be trusted. Build exception-based analytics that detect when an outcome deviates from its expected value in a statistically significant way, using seasonality-aware baselines, forecast residuals, control limits, and anomaly detection rather than static thresholds. Route those exceptions to accountable owners with context, likely drivers, and a recommended next action; actively tune sensitivity and volume to prevent alert fatigue and preserve signal. Design and deploy analytic agents that proactively monitor data, investigate variances, assemble narrative explanations, and deliver insight into the tools where people already work. Shift the organization's consumption model from pull to push: the measure of success is not how many people opened a dashboard, but whether the right person was told the right thing at the right time. Cross-Functional Partnership, Intake, and Prioritization Operate as a true partner to Product Management: contribute to roadmap, requirements, user research, and release planning, and run analytics with a product mindset covering personas, adoption metrics, and asset lifecycle management. Partner with Analytics Operations to run a transparent intake, triage, sizing, and prioritization process, with published capacity, explicit tradeoffs, and reliable delivery commitments. Make capacity constraints visible to stakeholders and executives, drive reuse over one-off builds, and decline or defer work with evidence rather than friction. Serve as a senior, executive-facing partner to business functions, translating ambiguous business questions into well-scoped analytic solutions. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field; equivalent professional experience will be considered. 15+ years of progressive experience in data, analytics, or business intelligence, including 8+ years leading teams and 4+ years managing managers. Demonstrated experience leading an organization of 25 or more people in a large, matrixed enterprise. Strong hands-on foundation in SQL, dimensional modeling, and ELT/ETL design, with production experience on a modern cloud data warehouse or lakehouse (for example Snowflake, Databricks, BigQuery, Redshift, or Synapse) and a transformation framework such as dbt. Experience applying software engineering practices to analytics work, including Git-based workflows, automated testing, and CI/CD. Enterprise-scale leveraging of BI and data visualization platforms such as Domo, Tableau, Power BI, or Looker, including governance, provisioning, adoption, and cost management. Demonstrated ability to participate in driving data governance program covering catalog, lineage, glossary, stewardship, quality, and access, using platforms such as Atlan, Collibra, Alation, or Informatica. Proven track record of delivering jointly with Data Engineering and Product Management, with clear ownership boundaries and shared accountability. Direct experience partnering with Data Science, including operationalizing, visualizing, and monitoring model output for business consumption. Working command of the statistical concepts underlying exception detection, including hypothesis testing, confidence intervals, variance and control limits, seasonality, and forecasting. Experience running a formal intake, prioritization, and capacity planning process for a shared services or platform organization. Excellent executive communication and influence skills, with the ability to operate effectively amid ambiguity and competing priorities. Experience managing budget, vendor contracts, and platform licensing. Preferred Skills: Master's degree or MBA in a related field. Production experience delivering LLM-based analytics: retrieval-augmented generation over governed data, text-to-SQL or conversational BI, semantic layers designed for model consumption, and prompt, evaluation, and cost monitoring frameworks. Experience designing agentic workflows and orchestration for monitoring, investigation, and notification use cases. Hands-on experience with Atlan, Domo, and Tableau specifically. Proficiency in Python or R for prototyping, and familiarity with common statistical and ML libraries and MLOps concepts. Experience deploying anomaly detection at scale, including alert routing, suppression, and fatigue management. Familiarity with data product and data mesh operating models, domain-aligned ownership, and data contracts. Experience operating in an Agile or product operating model at scale, including portfolio, OKR, and roadmap management. Deep experience with the “Silicon Valley” school of Product Management, as exemplified by the “Marty Kagan”-style academic approach a significant plus. Experience leading global or matrixed teams, including offshore or vendor-partnered delivery models. Track record leading a major platform migration, consolidation, or reporting rationalization effort. Demonstrated success attracting, developing, and retaining senior technical talent in a competitive market. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Требования к кандидату: - 6+ years commercial Data Engineering - Enterprise-scale data pipelines & platforms - Microsoft Azure data services - Azure Databricks + Apache Spark - Azure Data Factory - Microsoft Fabric + modern cloud analytics - Azure Data Lake (ADLS) or equivalent - Strong SQL + ETL/ELT - Medallion architecture + reusable frameworks - CI/CD & DevOps (Azure DevOps preferred)

Location: Indianapolis, United States; Chicago, United States; Cincinnati, United States; Columbus, United States; West Lafayette, United States; Bloomington, United States Location: Indianapolis, IN Metro (Hybrid / 3-Day Onsite) (Open to Regional/EST Candidates with Onsite Travel) Contract Type: Contractor Full-Time / Enterprise Project Engagement (Outsourced via Xenon7) About Xenon7 Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth. Job Summary We are seeking a Senior Machine Learning Engineer with extensive experience in production MLOps, model deployment, and system scaling to drive ML engineering initiatives for a top-tier life sciences client. This role sits at the critical intersection of production ML infrastructure, life science research, and manufacturing process engineering. In this position, you will own the architectural design and hands-on execution of production ML systems, model integration APIs, and scalable MLOps pipelines. You will bridge complex domains—from computational biology, small and large molecule research, and clinical trial analytics to active pharmaceutical ingredient (API) manufacturing processes, batch optimization, and industrial automation ML. Operating in a 3-day onsite hybrid capacity in Indianapolis, you will collaborate directly with process engineers, life science researchers, and platform engineering teams to build robust, low-latency ML systems that scale across the enterprise. Key Responsibilities Production MLOps & Systems Architecture Design, deploy, and maintain robust, production-grade MLOps pipelines and infrastructure for continuous model training, deployment, versioning, and monitoring. Implement automated model drift detection, performance monitoring, and self-healing inference pipelines in high-reliability environments. Process Engineering & Manufacturing ML Integration Operationalize and integrate production ML models into operational technology (OT), API manufacturing workflows, and chemical process control systems. Deploy predictive models for batch processing, process control optimization, real-time quality assurance, and facility automation use cases. Scalable Inference & System Integration Build low-latency, high-throughput microservices and serving architectures (FastAPI, Triton Inference Server, TorchServe) for model deployment into live production applications. Containerize and orchestrate ML workloads across distributed cloud and edge systems using Kubernetes, Docker, and modern pipeline engines (Kubeflow, MLflow). Technical Leadership & Domain Alignment Partner directly with chemical engineers, computational biologists, and software architects to translate operational friction into production-ready ML engineering solutions. Establish enterprise MLOps standards, model governance, and CI/CD best practices across the full machine learning operational lifecycle. Requirements Experience & Mindset Experience: Senior-level proficiency (10–20+ years) in software engineering, MLOps, production ML system deployment, and infrastructure scaling. Domain Adaptability: Demonstrated ability to deploy and maintain production ML systems across non-standard, highly specialized domains (e.g., transition between process/chemical engineering ML and clinical/scientific research applications). Location & Work Auth: Must hold unrestricted US Work Authorization (no sponsorship available) and be able to work 3 days per week onsite in the Indianapolis, IN area. Culture & Communication: Pragmatic problem-solving mindset, strong collaborative drive, and the ability to articulate complex MLOps architecture to cross-functional engineering teams. Must-Have Technical Stack Languages & Frameworks: Advanced Python, C++, and deep proficiency with PyTorch, TensorFlow, or Scikit-learn. MLOps & Serving: Proven expertise with Triton Inference Server, TorchServe, MLflow, Kubeflow, or Databricks ML runtime. Infrastructure & Orchestration: Hands-on expertise with Kubernetes, Docker, CI/CD pipelines, FastAPI/gRPC, and cloud platform ecosystems (AWS/Azure). Monitoring & Integration: Experience building real-time model monitoring, feature stores, drift detection systems, and integration with enterprise data pipelines. Domain Competency (Scientific & Process Focus) Deep exposure to applying ML models in either scientific/clinical domains (drug discovery, small/large molecule, computational biology) OR chemical/process engineering environments (API manufacturing, batch processing, SCADA/MES integration, process optimization). Nice-to-Haves & Certifications Academic background in Chemical Engineering, Bio-process Engineering, Computer Science, or a related STEM discipline. Direct experience operationalizing ML models inside regulated GxP environments in the Life Sciences or Specialty Chemicals sectors. Certifications: AWS Certified Machine Learning – Specialty, Databricks Certified Machine Learning Professional, or equivalent MLOps credentials. What This Role Is NOT Not a Data Scientist or Exploratory R&D Specialist: You will not be focusing on exploratory data analysis, academic algorithms, or standalone Jupyter notebook modeling; you are building, scaling, and maintaining production MLOps pipelines, inference engines, and model integration code. Not a non-coding Architect: This is a 100% hands-on MLOps and software engineering lead role requiring direct model deployment, infrastructure creation, and technical execution. Not a Fully Remote Position: This role requires a steady hybrid commitment of 3 days onsite per week at the client site in Indianapolis.

Location: Indianapolis, United States; Chicago, United States; Cincinnati, United States; Columbus, United States; West Lafayette, United States; Bloomington, United States Location: Indianapolis, IN Metro (Hybrid / 3-Day Onsite) (Open to Regional/EST Candidates with Onsite Travel) Contract Type: Contractor Full-Time / Enterprise Project Engagement (Outsourced via Xenon7) About Xenon7 Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth. Job Summary We are seeking a Senior Data Engineer with extensive experience in data architecture and platform engineering to drive data initiatives for a top-tier life sciences client. This role sits at the critical intersection of scientific research informatics, clinical data systems, and manufacturing process engineering. In this position, you will own the architectural vision and hands-on execution of scalable data platforms and pipelines. You will bridge complex data domains—from small and large molecule research, genomics, and clinical trial datasets to active pharmaceutical ingredient (API) manufacturing processes, batch data, and industrial control systems. Operating in a 3-day onsite hybrid capacity in Indianapolis, you will collaborate directly with process engineers, clinical scientists, and platform teams to build high-performance data infrastructure that accelerates drug discovery and manufacturing operations. Key Responsibilities Scientific & Clinical Data Platform Architecture Design, build, and maintain production-grade data pipelines and architecture tailored for scientific, clinical trial, and research informatics data (small/large molecule, genomics, proteomics, LIMS). Structure complex, multi-modal clinical and scientific datasets to enable advanced analytics, enterprise reporting, and downstream machine learning models. Process Engineering & Manufacturing Integration Ingest, harmonize, and model operational technology (OT) and manufacturing process datasets, including API manufacturing pipelines, batch processing data, MES, SCADA, and OSIsoft PI systems. Unify disparate laboratory and facility data pipelines into centralized, highly available enterprise data platforms. Enterprise Data Engineering & Compliance Build robust ETL/ELT pipelines using modern cloud platforms (Databricks, Snowflake, AWS/Azure), PySpark, and SQL. Ensure all data pipelines and platform integrations strictly adhere to enterprise governance, data residency, and GxP regulatory standards within a heavily monitored environment. Technical Leadership & Domain Alignment Partner directly with process engineers, chemical engineering leads, and research informatics directors to translate operational friction into robust technical specifications. Establish engineering best practices, data modeling standards, and pipeline monitoring frameworks across the enterprise data stack. Requirements Experience & Mindset Experience: Senior-level proficiency (10–20+ years) in software development, data platform architecture, and complex ETL/ELT engineering. Domain Adaptability: Demonstrated ability to engineer data pipelines across non-standard, highly specialized domains (e.g., transition between process/chemical engineering data and clinical/scientific research informatics). Location & Work Auth: Must hold unrestricted US Work Authorization (no sponsorship available) and be able to work 3 days per week onsite in the Indianapolis, IN area. Culture & Communication: Exceptional problem-solving mindset, strong adaptability, and the ability to articulate complex technical architecture to cross-functional engineering teams. Must-Have Technical Stack Languages & Frameworks: Advanced Python, PySpark, and expert-level SQL. Data Platforms: Hands-on expertise with Databricks, Snowflake, or AWS/Azure enterprise data ecosystems. Orchestration & ETL: Extensive experience with Airflow, dbt, Spark, and enterprise data orchestration engines. Data Pipelines: Proven track record building streaming and batch data architectures via REST APIs, message brokers, and database integrations. Domain Competency (Scientific & Process Focus) Deep exposure to either scientific/clinical informatics (CDISC/SDTM, LIMS, clinical trials, multi-omics) OR chemical/process engineering data (API manufacturing, batch data, SCADA, MES, OSIsoft PI). Nice-to-Haves & Certifications Academic background in Chemical Engineering, Bio-process Engineering, Computer Science, or a related STEM discipline. Direct experience working inside regulated GxP environments in the Life Sciences or Specialty Chemicals sectors. Certifications: Databricks Certified Data Engineer Senior/Professional, Snowflake SnowPro Core/Advanced, or AWS Data Engineer Associate/Professional. What This Role Is NOT Not a pure Data Scientist or ML Researcher: You will not be building or training machine learning models; you are designing and scaling the underlying data architecture, pipelines, and platform infrastructure. Not a non-coding Architect: This is a 100% hands-on engineering lead role requiring direct pipeline construction and technical execution. Not a Fully Remote Position: This role requires a steady hybrid commitment of 3 days onsite per week at the client site in Indianapolis.

Задачи: — Администрирование, конфигурация, оптимизация и поддержка платформы Databricks. — Управление рабочими пространствами Databricks в средах разработки, тестирования и продакшена. — Конфигурация и управление кластерами, пулами, заданиями и рабочими процессами для поддержки ETL, потоковых и ML задач. — Мониторинг состояния платформы, емкости и производительности, проактивное выявление и устранение проблем. — Управление версиями Databricks runtime, библиотеками и интеграциями с облачным хранилищем и сервисами данных. — Реализация и поддержка процедур резервного копирования, восстановления и обеспечения непрерывности бизнеса. — Настройка и поддержка управления идентификацией и доступом (IAM) в Databricks. — Внедрение и соблюдение лучших практик безопасности, включая шифрование, сетевой контроль и политики доступа к данным. — Сотрудничество с командами безопасности и соответствия для соблюдения организационных и нормативных требований. — Поддержка стандартов управления данными (например, Unity Catalog). — Оптимизация конфигураций кластеров, автоскейлинга и планирования заданий для баланса производительности и затрат. — Анализ метрик использования и затрат, внедрение стратегий контроля затрат. — Рекомендации и реализация стратегий настройки и оптимизации платформы для больших данных. — Взаимодействие с инженерами данных, аналитиками и дата-сайентистами для понимания требований и рекомендаций по использованию Databricks. — Предоставление поддержки уровня Tier 2/3 по инцидентам и запросам, связанным с Databricks. — Разработка и поддержка документации, инструкций и стандартных операционных процедур. — Проведение обучения пользователей и обмен знаниями по возможностям и лучшим практикам Databricks. — Автоматизация развертывания рабочих пространств и кластеров, конфигураций и политик с использованием Infrastructure as Code (Terraform, ARM/Bicep, CloudFormation). — Интеграция Databricks с CI/CD пайплайнами для развертывания кода и управления средами. — Поддержка лучших практик контроля версий для ноутбуков, заданий и конфигураций. Требования: — Высшее образование в области компьютерных наук, информационных систем, инженерии или смежных областях либо дополнительный опыт работы 4 года при отсутствии диплома. — Опыт работы не менее 8 лет в администрировании облачных платформ данных или сред больших данных. — Практический опыт администрирования Databricks (Azure, AWS или GCP Databricks). — Глубокое понимание рабочих пространств, кластеров, заданий, пулов и ноутбуков Databricks. — Знание облачных хранилищ (Azure Data Lake Storage, S3, GCS) и сетевых концепций. — Опыт управления идентификацией и доступом в соответствующем облачном провайдере (Azure AD, IAM и др.). — Навыки скриптинга и автоматизации (Python, PowerShell, Bash). — Знакомство с концепциями Spark (кластеры, исполнители, задания, партиции) и вопросами производительности. — Опыт мониторинга и устранения проблем с производительностью и надежностью платформы. — Сильные аналитические и проблемно-ориентированные навыки. — Умение объяснять сложные технические концепции технической и нетехнической аудитории. — Ориентация на клиента и качество сервиса. — Способность работать самостоятельно и в команде в динамичной agile-среде. Желательные квалификации: — Сертификация Databricks (например, Databricks Certified Data Engineer Associate/Professional, Lakehouse Fundamentals, Administrator). — Опыт работы с Unity Catalog и тонкой настройкой доступа к данным. — Опыт работы с CI/CD инструментами (Azure DevOps, GitHub Actions, Jenkins). — Опыт работы с Infrastructure as Code (предпочтительно Terraform). — Опыт работы с инструментами агрегации логов и мониторинга (Azure Monitor, CloudWatch, Datadog, Splunk). — Знание Delta Lake, структурированного стриминга и архитектур Lakehouse. — Опыт работы в корпоративных средах с высокими требованиями к безопасности и соответствию. Условия: — Удаленная работа из любой точки. — Полная занятость, 40 часов в неделю. — Требуется получение и поддержание уровня безопасности Public Trust с обязательной процедурой снятия отпечатков пальцев. — Требования к резидентству в США: проживание в США или территориях последние 5 лет с ограничениями на время отсутствия. — Конкурентная зарплата в диапазоне $10,669 – $14,435 в месяц ($128,039 - $173,229 в год), зависит от опыта и местоположения. — Пакет социальных льгот, включая медицинское страхование, 401(k) с компанией-матчем, оплачиваемый отпуск и другие выплаты. — Гибкий график работы и поддержка баланса работы и личной жизни. — Процесс верификации личности с использованием биометрии и ИИ для предотвращения мошенничества.

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We're looking for a Senior/Staff Analytics Engineer to join our growing Data team and lead the evolution of our Analytics Engineering platform. As Render scales, you'll build the foundations that turn raw data into trusted, reusable models for analytics, executive reporting, and AI-assisted decision-making. In this role, you'll partner closely with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions. Analysts and scientists will bring domain expertise and own business logic within their areas; you'll own the technical architecture, modeling standards, and engineering practices that help that work scale reliably. As a Senior/Staff-level individual contributor, you'll set the technical direction for Analytics Engineering at Render—strengthening data quality, improving the developer experience, and building semantic and context layers that make data easier to discover and use. You'll help teams move faster with consistent metrics and maintainable models they can trust. WHAT YOU'LL DO - Own our Analytics Engineering architecture. Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so our data remains trusted, scalable, and ready for AI-assisted analytics. - Build trusted, reusable data models. Design, build, and maintain governed dbt models that serve as authoritative sources for business-critical metrics across Product, Engineering, Growth, Go-to-Market, Finance, and other teams. - Establish engineering standards. Define and improve practices for data modeling, testing, documentation, version control, CI/CD, and code review. Review high-impact dbt changes and reduce technical debt across the analytics codebase. - Enable self-service and AI-assisted analytics. Design and maintain semantic and context layers that make metrics consistent, data discoverable, and analysis reliable for both people and AI tools. - Partner closely with analysts and scientists. Help analysts and scientists translate domain-specific business logic into scalable, maintainable warehouse models, moving shared logic out of individual reports and dashboards and into governed datasets. - Improve reliability and efficiency. Partner with Data Engineering to strengthen source data quality, warehouse architecture, and BigQuery performance and cost efficiency. - Raise the bar for Analytics Engineering. Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices, and help teams adopt shared standards. WHAT WE'RE LOOKING FOR - 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, including at least 3 years of hands-on experience running dbt in production. - Expert-level SQL skills and a track record of designing and owning scalable Kimball dimensional models. - Deep expertise in modern Analytics Engineering practices, including Git, testing, CI/CD, documentation, data contracts, lineage, and governance. - Experience building semantic and context layers, trusted metrics, and warehouse architectures that support self-service analytics for humans and AI agents across multiple business domains. - Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency, with experience in platforms such as BigQuery, Databricks, or Snowflake. - A track record of establishing technical standards, influencing engineering practices without formal authority, and improving reliability while reducing technical debt. - Proven ability to partner closely with analysts, scientists, and business stakeholders to translate requirements into scalable, maintainable data models. - Excellent communication skills. You can explain complex technical concepts and tradeoffs to technical and non-technical audiences and build alignment across teams. - Experience building data models that connect product usage, acquisition, CRM, and financial data across the customer lifecycle. - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate data modeling, testing, documentation, or exploration. NICE-TO-HAVES - Hands-on experience with Render’s analytics stack, including BigQuery, Segment, dbt, and analytics tools such as Metabase or Mixpanel. - Experience with developer-focused, product-led, sales-led, or usage-based businesses. - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Задачи: – Разработка, создание и поддержка масштабируемых конвейеров обработки данных с использованием Apache Spark и современных платформ обработки данных. – Разработка и оптимизация архитектур хранилищ данных для поддержки рабочих процессов анализа данных и машинного обучения. – Внедрение моделей и структур данных, обеспечивающих качество, согласованность и доступность данных. – Сотрудничество со специалистами по анализу данных и аналитиками для понимания потребностей в данных и предложения решений. – Обеспечение безопасности данных и соответствия нормативным требованиям. – Мониторинг и устранение неполадок, связанных с производительностью и надежностью конвейера обработки данных. – Постоянное совершенствование процессов и передовых методов обработки данных. – Взаимодействие с межфункциональными командами и участие в технических дискуссиях. – На руководящей должности оказание технической поддержки и наставничество младших инженеров. Требования: – Опыт работы с Python или Scala/Java. – Углубленные знания SQL. – Практический опыт работы с Apache Spark, Databricks, Snowflake или Microsoft Fabric. – Понимание концепции и архитектуры хранилища данных (data lakehouse). – Понимание основ распределенных систем. – Навыки моделирования данных и создания хранилищ данных. – Опыт работы с облачными архитектурами данных на платформах AWS, Azure или GCP. – Готовность к обучению и экспериментам с разными решениями. – Ценить баланс между работой и личной жизнью, избегать сверхурочной работы. – Умение просить о помощи и работать в команде.

Location: New York, New York, United States About the Role iCapital is looking to hire a Data Engineering Senior Vice President, to lead the evolution of the enterprise data platform that powers AI, automation, analytics, and data-driven decision making across the firm while positioning proprietary data as a strategic business asset. This role is responsible for defining and executing the architectural vision, roadmap, and operating model for a modern, AI-ready data ecosystem built on a strong foundation of cloud technologies and established engineering capabilities. The position will provide leadership across platform architecture, engineering standards, and cross-functional alignment while overseeing the development of scalable data products, semantic layer capabilities, and future AI enablement initiatives. Partnering closely with an engaged executive steering committee, this individual will play a critical role in shaping how data supports the firm's long-term growth and innovation strategy. Responsibilities Define and own iCapital's enterprise data architecture, including the Snowflake platform, semantic layer, reusable data products, and AI-ready ecosystem. Establish standards for data engineering, governance, security, observability, quality, and documentation. Own platform reliability, SLAs, DataOps practices, and incident management. Lead architectural strategy, tooling decisions, and platform investment recommendations. Develop and execute the multi-year Data Engineering roadmap aligned to business and AI priorities. Translate enterprise data strategy into prioritized engineering initiatives and platform capabilities. Build business cases for platform investments and proactively address technical debt and future scalability needs. Partner with business and technology leaders to deliver data products that support enterprise objectives. Communicate platform progress, risks, and investment decisions to executive stakeholders. Build and lead a high-performing Data Engineering organization and culture. Qualifications 12+ years of experience in data engineering, including 5+ years leading large-scale engineering organizations across multiple functions Proven track record designing, building, and operating enterprise-scale cloud data platforms (Snowflake, Databricks, or equivalent), including architecture, security, governance, and cost optimization Deep expertise establishing data engineering best practices across pipeline design, data quality, observability, data contracts, documentation, and operational support Demonstrated success developing multi-year platform strategies, securing investment, prioritizing initiatives, and delivering measurable business outcomes Experience partnering with and presenting to executive stakeholders within regulated industries, translating complex technical concepts into business impact Hands-on experience with analytics engineering, semantic layer development, and modern data transformation frameworks such as dbt Financial services experience within asset management, wealth management, fintech, banking, or insurance, including knowledge of regulated data environments and governance requirements Deep expertise in Snowflake architecture, performance optimization, security, and data sharing at enterprise scale Knowledge of alternative investments, wealth management, fund administration, or related financial services domains Experience building AI- and ML-enabled data platforms, including semantic layers, feature stores, model-serving infrastructure, or LLM-integrated architectures Experience with Informatica or comparable enterprise data catalog, metadata management, and MDM platforms Proven success scaling data engineering organizations through periods of rapid growth, including organizational design, hiring, and leadership development Benefits The base salary range for this role is $200,000 to $250,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Location: United States; Denver; Chicago; Seattle; Austin; Phoenix; New York; Los Angeles; Boston; San Francisco Workplace: Remote Recognized on the 2025 Forbes Cloud 100 list https://www.forbes.com/companies/clickhouse/?list=cloud100, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and $250M ARR https://clickhouse.com/blog/clickhouse-tops-250m-arr-and-4000-customers, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads. The company's sustained, accelerating momentum was recently validated by a $400M Series D financing round https://clickhouse.com/blog/clickhouse-raises-400-million-series-d-acquires-langfuse-launches-postgres. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We're on a mission to transform how companies use data. Come be a part of our journey! We're hiring a Product Manager to own partner integrations at ClickHouse. This role owns how ClickHouse shows up inside the platforms our customers already use: embedded, native experiences across the hyperscalers and developer platforms, and deeper technical integrations with strategic partners like dbt, Fivetran, Hex, and Sigma. There is a growing surface of partner work already in motion, and this role shapes where we invest in co-innovation opportunities. This is one of the most cross-functional roles at ClickHouse. You'll work across multiple engineering teams, our partnerships and solutions teams, and the partners themselves to deliver meaningful co-innovation and integrations with complementary technologies. You'll own the technical side of our House Mates partner program and be the person who navigates the multi-org reality of getting an integration certified, listed, and live. This is a hands-on role: you'll write the specs, run the partner calls, drive certification processes, and coordinate across teams to get things over the line. YOU WILL - Own the product strategy, roadmap, and execution for ClickHouse's Cloud integrations with strategic partners - Seek out complementary innovation opportunities with partners. Define what a "better together" integration looks like with each strategic partner, and drive it from joint roadmap through launch. - Navigate the trade-offs of embedded integrations: billing and metering, identity and auth, security and data residency, and coordination across ClickHouse and partner teams. - Project-manage complex, multi-org launches: marketplace listings, certification processes, partner co-marketing, and GA timelines across multiple organizations. - Own the technical standards and certification criteria for integrations submitted through the House Mates partner program. - Measure and communicate co-innovation business impact, adoption and product strategy to executive leadership. - Represent ClickHouse externally at partner events and in joint content. YOU BRING - Experience shipping integrations into third-party platforms before: hyperscaler marketplaces, embedded or native integrations, ISV partnerships, or OEM/white-label work. - An understanding of the trade-offs that make or break a partner integration, billing, auth, security, cross-team dependencies, and have made those decisions in the past. - A strong project management lens and are comfortable owning a launch that depends on five teams across two companies. - Patience and resilience with partners who are unresponsive or have their own competing priorities, and you find creative ways to keep things moving anyway. - Technical ability to understand an integration end to end, from provisioning and auth to billing and data flow, and to hold a credible conversation with engineers about APIs, architecture, and technical trade-offs. - Energy and excitement for external-facing work: partner calls, customer conversations, and representing the product publicly. - Hands-on and high ownership ability. You write the specs, run the partner calls, and stay close to the details. - Comfort in ambiguity and fast-moving environments. PREFERRED QUALIFICATIONS - Hands-on experience building partner integrations with hyperscalers and modern technology companies. - Experience running or supporting a technology partner program. - Background at a database or data infrastructure company; familiarity with ClickHouse or peers like Snowflake, BigQuery, or Databricks. - Experience working in remote, multi-timezone environments. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Remote, DC MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data. The Federal Field Architect at MinIO will bridge our technical platform and the mission requirements of our federal customers. You will bring deep technical expertise to bear across DoW, IC, and civilian agency engagements, spanning data infrastructure for both traditional workloads and AI training and inference at scale, working closely with our Federal Partner Sales team along with Engineering, Support, our channel and systems integrator partners, and our technology ecosystem partners, to ensure customers succeed from Proof of Value through production and beyond, including in air-gapped, classified, and DDIL (Denied, Degraded, Intermittent, Limited) environments. What You Will Do: Technical Architecture & Design: Architect AIStor deployments for federal customers, spanning on-prem, air-gapped, sovereign cloud, and tactical edge environments, including erasure coding, tiering, and replication topology design. Federal Compliance Expertise: Serve as the technical authority on FIPS 140-3, FedRAMP, NIST 800-53, and Zero Trust alignment, translating compliance requirements into deployable architecture for agency customers and partners. Proof of Value & Technical Validation: Lead PoVs, technical demonstrations, and reference architecture design for DoW, IC, and civilian agency opportunities, in direct engagement with customers and through our channel partner and FSI ecosystem. Partner Enablement: Provide technical training and architecture guidance to our federal reseller, systems integrator (FSI), and technology ecosystem partners, ensuring they can independently represent and deploy MinIO solutions with confidence. Ecosystem & Technology Partnerships: Serve as the technical point of contact for joint architecture work with ecosystem partners (e.g., NVIDIA, Databricks, Supermicro), supporting joint solutions, reference architectures, and co-sell motions. Kubernetes & Cloud-Native Deployment: Guide customers and partners on deploying AIStor across Kubernetes distributions common in federal environments, including OpenShift and Rancher. AI/ML Data Infrastructure: Architect data infrastructure for AI training, fine-tuning, and large-scale data lake workloads, ensuring GPU clusters stay fully fed and utilized rather than data-starved. Inference & Agentic AI Enablement: Advise on architecture that reduces recompute overhead and maximizes GPU utilization during inference at scale, including context memory strategies for agentic and long-running AI workloads. Technical Content Development: Develop reference architectures, technical white papers, and solution briefs that support the Federal Partner Sales team and our partner network in active pursuits. Your Skills and Experience: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. 4+ years in a solutions architect, sales engineering, or field engineering role, preferably within cloud, storage, or federal systems integration. Active security clearance strongly preferred; ability to obtain a clearance required. Deep technical knowledge of object storage (S3-compatible platforms), Kubernetes, and cloud-native/on-prem hybrid architectures. Familiarity with GPU-accelerated infrastructure and the data/memory demands of AI training and inference workloads at scale. Familiarity with federal compliance frameworks (FIPS 140-3, NIST 800-53, FedRAMP) and DoW/IC deployment environments (air-gapped, classified, DDIL). Strong technical acumen with the ability to communicate complex architecture decisions clearly to both technical and non-technical stakeholders. Experience working through or alongside channel partners, FSIs, and technology ecosystem partners (e.g., NVIDIA, Databricks) is a plus. What We Offer: Health Care Plan (Medical, Dental & Vision) 401K with 3% Contribution Pre-IPO Stock Options At least 12 Public Holidays Flexible Time Off Equal Opportunity Policy (EEO) MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

Location: Milan, Italy; Biassono, Italy Workplace: Hybrid Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. 🚀 THE ADVENTURE AHEAD As our Data Engineer I, you will build and fine-tune the robust cloud data pipelines that power our analytics, data science, and product teams. You’ll tackle real-world architecture challenges, collaborate with world-class engineers, and directly shape how intelligent learning experiences reach millions of users worldwide. We are seeking engineers who bring deep analytical rigor to data modeling and relentless dedication to data quality.   🛠️ THE DAY-TO-DAY - Engineer the Flow: Implement high-performance ELT/ETL transformations using tools like dbt based on innovative specs from senior engineers and architects. - Orchestrate Data Jobs: Build, deploy, and maintain seamless data ingestion and transformation jobs powered by Airflow and Cloud Composer. - Guard Data Quality: Write and execute vital data tests—including row counts, null checks, and reference validations—to keep our datasets clean and trusted. - Monitor & Resolve: Proactively investigate automated alerts, ensuring peak system performance and escalating deeper architectural changes when needed. - Shape Lakehouse Architecture: Maintain pristine schemas and naming conventions across Snowflake, BigQuery, or Databricks while implementing table and view enhancements. - Document & Empower: Create clear documentation for pipelines, schemas, and caveats so the entire engineering team can safely build on your foundation. - Partner & Collaborate: Work closely alongside Analytics and Data Science teams to deeply understand their query needs and deliver optimized data structures. ⚡ YOUR SUPERPOWERS - Solid Academic & Technical Foundation: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience). - Early Career Momentum: 2-3 years of hands-on experience in data engineering, BI engineering, or equivalent project-driven environments. - SQL Mastery: Exceptional ability to write clean SQL (joins, filters, aggregations) and query across cloud data platforms like Snowflake, BigQuery, or Databricks. - ETL/ELT Aptitude: Strong foundational understanding of data transformation concepts and comfort navigating tools like dbt and Airflow under guided supervision. - Code & Version Control Literacy: Familiarity with Python (or similar languages) and Git-based collaborative workflows to ship clean code efficiently. OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing.   OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul.   OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Fuel for Your Day: Receive a meal voucher for every working day, so you can focus on doing your best work while enjoying a meal that keeps you energized. - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long.

Location: Toronto, Ontario Workplace: Hybrid Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. 🚀 THE ADVENTURE AHEAD As our Data Engineer I, you will build and fine-tune the robust cloud data pipelines that power our analytics, data science, and product teams. You’ll tackle real-world architecture challenges, collaborate with world-class engineers, and directly shape how intelligent learning experiences reach millions of users worldwide. We are seeking engineers who bring deep analytical rigor to data modeling and relentless dedication to data quality. 🛠️ THE DAY-TO-DAY - Engineer the Flow: Implement high-performance ELT/ETL transformations using tools like dbt based on innovative specs from senior engineers and architects. - Orchestrate Data Jobs: Build, deploy, and maintain seamless data ingestion and transformation jobs powered by Airflow and Cloud Composer. - Guard Data Quality: Write and execute vital data tests—including row counts, null checks, and reference validations—to keep our datasets clean and trusted. - Monitor & Resolve: Proactively investigate automated alerts, ensuring peak system performance and escalating deeper architectural changes when needed. - Shape Lakehouse Architecture: Maintain pristine schemas and naming conventions across Snowflake, BigQuery, or Databricks while implementing table and view enhancements. - Document & Empower: Create clear documentation for pipelines, schemas, and caveats so the entire engineering team can safely build on your foundation. - Partner & Collaborate: Work closely alongside Analytics and Data Science teams to deeply understand their query needs and deliver optimized data structures. ⚡ YOUR SUPERPOWERS - Solid Academic & Technical Foundation: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience). - Early Career Momentum: 2-3 years of hands-on experience in data engineering, BI engineering, or equivalent project-driven environments. - SQL Mastery: Exceptional ability to write clean SQL (joins, filters, aggregations) and query across cloud data platforms like Snowflake, BigQuery, or Databricks. - ETL/ELT Aptitude: Strong foundational understanding of data transformation concepts and comfort navigating tools like dbt and Airflow under guided supervision. - Code & Version Control Literacy: Familiarity with Python (or similar languages) and Git-based collaborative workflows to ship clean code efficiently. OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing. OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul. OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long. ABOUT DOCEBO 💙 At Docebo, we create seamless, AI-powered learning experiences for over 3,000 customers worldwide. We have successfully achieved two IPOs (TSX: DCBO & NASDAQ: DCBO https://www.docebo.inc/home/default.aspx), been recognized as a top SaaS e-learning solution, and are growing exponentially in the process. We're a global company, with office across North America, EMEA, APAC, and beyond. Our team is guided by five core values—Grow Together Win Together, Build with Our Customer, Clear is Kind, Own Outcomes, Progress Over Perfection—that shape everything we do. If this resonates with you, now is the perfect time to join one of the fastest-growing learning technology companies in the world. Docebo is an Equal Employment Opportunity employer https://www.eeoc.gov/sites/default/files/2022-10/EEOC_KnowYourRights_screen_reader_10_20.pdf. We are committed to diversity and inclusion in our workforce. All qualified applicants and employees will receive consideration for employment regardless of their race, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, citizenship status, age, disability, genetic information, or any other category protected under applicable law. As a federal contractor, Docebo is committed to the principles of affirmative action and equal employment opportunity for protected veterans and individuals with disabilities. Docebo does not discriminate because of protected veteran status or on the basis of disability, and Docebo takes affirmative action to employ and advance in employment qualified protected veterans and individuals with disabilities. Any individuals requiring a reasonable accommodation or would like to voluntarily disclose a disability or protected veteran status to assist with their employment application should send an e-mail to their recruiter directly.

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: As a Senior / Staff Data Scientist, you will help shape how PlayStation measures the impact of products, features and commercial initiatives through world-class experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will develop innovative measurement methodologies, define best practices, and provide technical leadership that enables teams across PlayStation to make faster, more confident business decisions. This role goes beyond traditional A/B testing. You will solve complex measurement problems where controlled experiments are difficult or impossible, applying modern causal inference, statistical modelling and machine learning techniques to generate robust business insights. You will collaborate closely with product, engineering, analytics and business teams to raise the standard of experimentation and evidence-based decision-making across the organisation. This is an opportunity to influence strategic decisions impacting millions of PlayStation players while helping establish best-in-class measurement practices across one of the world's leading entertainment companies. What You'll Be Doing: Develop innovative measurement methodologies across experimentation, causal inference and advanced analytics that improve the quality, reliability and scalability of business decision-making across PlayStation. Design robust measurement approaches across randomised experiments, quasi-experimental methods and observational causal inference where controlled experimentation is impractical. Research, evaluate and prototype statistical, machine learning and AI techniques to solve complex real-world measurement challenges. Apply advanced data science and machine learning techniques where appropriate to complement experimentation and support complex business decisions. Define and promote best practices for experiment design, statistical analysis and causal measurement across multiple product and business teams, helping scale experimentation across PlayStation. Partner closely with senior business leaders, product managers, engineers and analysts to identify high-impact measurement opportunities and ensure product and commercial decisions are supported by rigorous evidence. Partner with engineering teams to influence the evolution of PlayStation's experimentation platform and measurement capabilities, ensuring statistical best practices are embedded into future platform development. Provide technical leadership across multiple product and commercial domains, influencing measurement strategy, analytical standards and long-term technical direction through expertise and collaboration. Mentor and develop analysts and data scientists, helping raise technical capability and analytical excellence across the team. Champion a culture of evidence-based decision-making by educating stakeholders, sharing best practices, and communicating advances in experimentation, causal inference and applied data science. Stay current with emerging developments in statistics, machine learning and AI, identifying opportunities to improve measurement capabilities and analytical workflows. Represent the team across PlayStation, building strong partnerships, engaging senior stakeholders, and promoting technical excellence in data science and experimentation. What We're Looking For: Required: Master's degree (or equivalent industry experience) in Statistics, Economics, Mathematics, Computer Science, Data Science or another quantitative discipline. PhD preferred. Strong industry experience (5+ years) applying experimentation, causal inference, statistical modelling and measurement science to solve complex business problems. Deep expertise in experimental design, A/B testing and modern causal inference methods, including quasi-experimental approaches. Experience applying advanced data science, machine learning and statistical modelling techniques to solve complex business problems. Expert-level proficiency in Python and SQL for large-scale analytical workflows. Experience developing reusable analytical methodologies, frameworks or libraries that improve measurement quality and consistency across teams. Demonstrated ability to influence technical direction, promote best practices and drive adoption through collaboration, technical leadership and senior stakeholder engagement. Strong stakeholder management, executive communication and influencing skills, with the ability to translate complex analytical concepts into clear business recommendations for both technical and non-technical audiences. Curiosity, creativity and a pragmatic approach to solving ambiguous, high-impact business problems. Preferred: Experience working in gaming, digital products, consumer technology, e-commerce or subscription businesses. Familiarity with modern data engineering and analytics tooling such as Databricks, Snowflake, Git and Airflow. Experience with modern business intelligence and data visualisation tools such as Tableau, Domo or Power BI. Experience applying AI tools, including large language models (LLMs), to improve data science workflows and analytical productivity. Demonstrated technical leadership through mentoring, publications, conference presentations, open-source contributions or internal communities of practice. What You'll Influence: Measurement strategy for PlayStation's largest product and commercial initiatives. Experimentation best practices adopted across multiple business functions. Strategic product and commercial decisions through rigorous causal evidence. The evolution of PlayStation's measurement and experimentation capabilities. Technical excellence in experimentation, causal inference and applied data science across the organisation. Why You'll Love This Role: Shape how PlayStation measures product and commercial success across a global business. Influence strategic decisions affecting millions of players worldwide. Solve challenging real-world problems using cutting-edge experimentation, causal inference and machine learning techniques. Collaborate with talented scientists, engineers and product leaders on high-impact initiatives. Drive the adoption of best practices in experimentation and evidence-based decision-making across PlayStation. Continue developing your technical expertise while mentoring and growing others. Benefits: Discretionary bonus opportunity Hybrid Working (FlexModes) Private Medical Insurance Dental Scheme 25 days annual leave On-site gym Subsidised café Complimentary soft drinks On-site bar Secure cycle storage and shower facilities Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Dublin, Dublin, Ireland, EMEA From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About the Role We’re looking for a Business Development Representative (BDR) to join our Dublin office and help accelerate pipeline generation. This role is ideal for someone with 9+ months of experience in technology sales who thrives in outbound prospecting, account research, and consultative discovery conversations. Experience selling into data, analytics, cloud, or infrastructure teams is a strong plus. As an BDR you’ll identify and engage target accounts, multi-thread into strategic organizations, and generate qualified pipeline through personalized outreach across phone, email, LinkedIn, and video. You’ll work directly with modern data leaders and technical buyers at fast-growing and enterprise organizations evaluating cloud data infrastructure, analytics modernization, AI initiatives, and data integration strategies. This is a full-time position based out of our Dublin office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Salesforce, Outreach, LinkedIn Sales Navigator, ZoomInfo, Lusha, Nooks, ChatGPT and AI prospecting tools, Gong, Google Workspace, Slack, Vidyard / Loom What You’ll Do Generate qualified pipeline through outbound prospecting across target accounts Research accounts, industries, and personas to craft personalized outreach Partner closely with Sales Directors to build account strategies and prioritize opportunities Execute multi-channel outbound campaigns using phone, email, LinkedIn, and video Conduct discovery conversations to uncover business challenges, technical pain points, and initiatives Engage data, analytics, engineering, IT, RevOps, and executive personas Maintain accurate activity, contact, and opportunity data within Salesforce Collaborate cross-functionally with Marketing, Partnerships, and Sales leadership Leverage AI tools and sales technologies to improve prospecting efficiency and messaging quality Consistently achieve and exceed activity, meeting generation, and pipeline targets Skills We’re Looking For 9+ months of experience in SaaS, cloud, infrastructure, or technology sales development Strong written and verbal communication skills with the ability to engage technical and business stakeholders Ability to learn and articulate technical concepts related to data, analytics, cloud, and AI infrastructure Experience with outbound prospecting and multi-threaded account engagement Strong organizational skills and ability to manage multiple accounts and priorities simultaneously Comfortable using AI tools such as ChatGPT or sales engagement platforms to improve research, messaging, and productivity Coachable, curious, resilient, and motivated by a high-performance sales environment French Speaking Bonus Skills Experience selling into data, analytics, engineering, or IT organizations Familiarity with modern data stack technologies such as Snowflake, Databricks, dbt, or cloud data warehouses Experience using Outreach, Sales Navigator, ZoomInfo, or Gong Previous experience working in a high-growth SaaS environment Demonstrated success exceeding outbound pipeline generation targets #LI-LA1 #LI-HYBRID Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: Dublin, Dublin, Ireland, EMEA From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About the Role We’re looking for a Business Development Representative (BDR) to join our Dublin office and help accelerate pipeline generation. This role is ideal for someone with 9+ months of experience in technology sales who thrives in outbound prospecting, account research, and consultative discovery conversations. Experience selling into data, analytics, cloud, or infrastructure teams is a strong plus. As an BDR you’ll identify and engage target accounts, multi-thread into strategic organizations, and generate qualified pipeline through personalized outreach across phone, email, LinkedIn, and video. You’ll work directly with modern data leaders and technical buyers at fast-growing and enterprise organizations evaluating cloud data infrastructure, analytics modernization, AI initiatives, and data integration strategies. This is a full-time position based out of our Dublin office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Salesforce, Outreach, LinkedIn Sales Navigator, ZoomInfo, Lusha, Nooks, ChatGPT and AI prospecting tools, Gong, Google Workspace, Slack, Vidyard / Loom What You’ll Do Generate qualified pipeline through outbound prospecting across target accounts Research accounts, industries, and personas to craft personalized outreach Partner closely with Sales Directors to build account strategies and prioritize opportunities Execute multi-channel outbound campaigns using phone, email, LinkedIn, and video Conduct discovery conversations to uncover business challenges, technical pain points, and initiatives Engage data, analytics, engineering, IT, RevOps, and executive personas Maintain accurate activity, contact, and opportunity data within Salesforce Collaborate cross-functionally with Marketing, Partnerships, and Sales leadership Leverage AI tools and sales technologies to improve prospecting efficiency and messaging quality Consistently achieve and exceed activity, meeting generation, and pipeline targets Skills We’re Looking For 9+ months of experience in SaaS, cloud, infrastructure, or technology sales development Strong written and verbal communication skills with the ability to engage technical and business stakeholders Ability to learn and articulate technical concepts related to data, analytics, cloud, and AI infrastructure Experience with outbound prospecting and multi-threaded account engagement Strong organizational skills and ability to manage multiple accounts and priorities simultaneously Comfortable using AI tools such as ChatGPT or sales engagement platforms to improve research, messaging, and productivity Coachable, curious, resilient, and motivated by a high-performance sales environment German Speaking Bonus Skills Experience selling into data, analytics, engineering, or IT organizations Familiarity with modern data stack technologies such as Snowflake, Databricks, dbt, or cloud data warehouses Experience using Outreach, Sales Navigator, ZoomInfo, or Gong Previous experience working in a high-growth SaaS environment Demonstrated success exceeding outbound pipeline generation targets #LI-LA1 #LI-HYBRID Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.