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Location: Belgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Odesa, Ukraine; Remote.BG, Bulgaria; Remote.PL, Poland; Riga, Latvia; Sofia, Bulgaria; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland We are looking for a Strong Middle / Senior Databricks Developer with Azure to build scalable data platforms, develop complex data pipelines, and support cloud based data engineering solutions. The Data Platform project focuses on delivering cloud based data engineering solutions in the Microsoft Azure ecosystem. You will work with Databricks, Spark, and Azure services to build and optimize reliable data pipelines and support modern Lakehouse architecture. Design data solutions using Databricks Develop data pipelines for structured and unstructured data Build ETL and ELT workflows in Azure Develop high performance solutions using PySpark and Spark SQL Design Lakehouse architectures using Delta Lake Integrate data from databases APIs cloud services and streaming platforms Optimize Spark workloads for performance scalability and cost efficiency Ensure data quality governance security and monitoring standards Collaborate with Data Engineers Data Architects Analytics teams and business stakeholders Participate in architectural discussions and technical decision making Support CI and CD processes and infrastructure automation practices 4+ years of experience in Data Engineering 3+ years of hands on experience with Azure Databricks Experience with Apache Spark and PySpark Knowledge of Python and SQL Experience with Azure Data Factory Experience with Azure Data Lake Storage Gen2 Experience with Delta Lake and Lakehouse architecture Experience implementing end to end data pipelines in Azure Understanding of data modeling principles and best practices Experience working with large scale datasets in cloud environments Experience with Git based version control systems Upper Intermediate or higher English level Experience optimizing Spark workloads Experience collaborating with cross functional technical and business teams Experience supporting CI and CD processes Experience with infrastructure automation practices

Location: Poland; Czechia; Bulgaria; Croatia; Romania; France About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role Our client is a Big4 Consultancy group that works with leading financial institutions on AI-driven transformation, automation, advanced analytics, and financial crime prevention . Their are building a production-grade AI-assisted KYC / Customer Due Diligence platform for an international insurance environment. We are looking for an experienced IT Solution Architect to own the technical design of the production solution across Azure and Databricks , including runtime architecture, networking, identities, environments, integration patterns, resilience, monitoring, service transition, and operational handover. CONTRACT: B2B or B2C contract COMMITMENT: Full-time, 3-4 months contract with possibility of extension or getting on new projects LOCATIONS: Remote, EU-based candidates START: ASAP PROCESS: Initial qualification followed by client interviews Responsibilities Design the production runtime architecture across Databricks and Azure. Define networking, identity, access, and environment architecture across dev, test, acceptance, and production. Design for availability, SLOs, monitoring, alerting, backup, restore, rollback, and operational resilience . Define safe write-back mechanisms and controls for business-critical integrations. Decide integration patterns together with client architects, including API Management, integration layers, asynchronous APIs, and callbacks . Define the operating model across L1/L2/L3 support, incident, change, and release management . Plan service transition and handover to local IT teams. Ensure the solution can be effectively supported after deployment. Represent the solution at architecture and design boards. Work closely with engineering, platform, security, operations, and country teams. Requirements Strong Azure solution architecture experience, including APIM, Entra ID, Key Vault, private endpoints, Log Analytics, and Application Insights. Strong hands-on architecture experience with Databricks , including Unity Catalog and Model Serving / AI Gateway. Experience with Infrastructure as Code using Terraform . Strong experience with CI/CD in Azure DevOps . Experience designing production systems for high availability, observability, backup, restore, and rollback. Strong understanding of enterprise integration patterns and API architecture. Experience defining ITIL-based operating models and service transition for critical systems. Strong ability to work with architecture boards and senior technical stakeholders. Fluent English and ability to work remotely within the EU.

Location: Poland; Czechia; Bulgaria; Croatia; Romania; France About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role Our client is a Big4 Consultancy group that works with leading financial institutions on AI-driven transformation, automation, advanced analytics, and financial crime prevention . Their are building a production-grade AI-assisted KYC / Customer Due Diligence platform for an international insurance environment. We are looking for an experienced Data / Integration Engineer to own the data flowing into and out of the platform. The role focuses on Databricks, Python / PySpark, SQL, data modelling, data contracts, APIs, legacy-system integration, and data quality , replacing mocked sources with reliable production integrations. CONTRACT: B2B or B2C contract COMMITMENT: Full-time, 3-4 months contract with possibility of extension or getting on new projects LOCATIONS: Remote, EU-based candidates START: ASAP PROCESS: Initial qualification followed by client interviews Responsibilities Inventory and map all internal and external data sources. Define data contracts and canonical data structures for client, screening, evidence, audit, and reporting data. Build connectors to external screening providers, public registers, and local data sources. Connect Databricks with SQL Server, legacy databases, and core enterprise systems. Support API, database-link, batch, file, and SFTP-based integrations. Design and maintain data models supporting evidence, audit trails, and reporting. Implement data quality checks, contract tests, and retention rules . Validate incoming and outgoing data flows across production services. Support integration troubleshooting and production-readiness activities. Contribute to a business-critical platform where data accuracy and reliability are essential. Requirements Strong hands-on experience with Databricks , including Delta Lake and Unity Catalog. Strong experience with Python / PySpark . Advanced SQL skills. Experience integrating with SQL Server and legacy databases . Strong experience with REST APIs, DB links, batch processing, files, and SFTP integrations . Experience with data modelling and data-contract design . Experience implementing data-quality validation and integration testing. Fluent English and ability to work remotely within the EU.

Location: United Kingdom We are EnerMech, a specialist service company that delivers safe, integrated solutions for complex energy projects. For over 50 years, we've been energizing our clients across the world with unrivalled expertise, equipment, and technology that supports the entire asset life-cycle - offshore and on land. We enable progress through our three global business lines: Energy Solutions, Infrastructure & Industrial Solutions, and Lifting Solutions. Within these areas, we offer a wide range of services, including cranes, lifting, fluid power, training, equipment rental, pipeline and subsea, process, and valves - all designed to help our clients optimize performance, enhance reliability, and improve efficiency. With a focus on operational excellence, we deliver value through our customized integrated solutions. This approach reduces risk and enhances efficiencies making us a leading and trusted partner every step of the way. The Role & Responsibilities The role will be responsible for taking technical ownership of key workstreams on EnerMech's Azure Databricks data platform, operating across the full platform stack: data modelling and pipeline development in Databricks, the underlying Azure infrastructure, and the CI/CD, DevOps and DataOps practices that keep the platform reliable, secure and scalable. The role holder operates with a high degree of autonomy, makes and documents architectural decisions, resolves complex platform issues, and is a technical point of contact for the global EBS Team, and business stakeholders. This is a fully remote role in the UK ,supporting our Enterprise Business Systems (EBS) function in the Mumbai Shared Service Centre. Key reponsibilities will include: Design, build, quality and reliable operation of assigned workstreams on the Azure Databricks data platform, from scoping through to production deployment. Integrity of the medallion data model (bronze/silver/gold) for assigned data domains, ensuring data is modelled, validated, documented and certified for downstream reporting and analytics. Build and optimise Delta tables and materialized views, with attention to performance at scale. Design and implement data quality frameworks (preferably DQX or equivalent), including quarantine/error handling and validation against data contracts. Define job-specific compute configurations appropriate to each workload, balancing performance and cost. Contribute to and troubleshoot Terraform-managed infrastructure (networking, storage, Key Vaults, Managed DevOps Pools, Dev Centers). Own and maintain Azure DevOps build and release pipelines, variable groups/libraries, and repository security, permissions and branch policies. Support environment-level Azure configuration, including subscription-level access, RBAC for user and pipeline (service principal) identities, and Terraform state backend management across multiple storage accounts and environments. Operate autonomously across a workstream, from scoping through to production deployment. Use AI-assisted tooling to support day-to-day development, validating outputs against authoritative sources (architecture decisions, technical leads, documentation) before acting on them. Communicate clearly with technical and non-technical stakeholders, including across time zones with colleagues in the UK, Americas, Middle East and Asia Pacific. The Requirements Essential Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline, or equivalent practical experience. Typically 6+ years in data engineering, including 3+ years hands-on with Azure Databricks in production. Demonstrated ownership of medallion architecture design and data modelling. Implemented data quality frameworks and data contracts in production. Implemented PII protection (masking, tokenisation or access tiering) across environments. Platform engineering experience: diagnosing infrastructure issues, not just consuming platform services. Track record of autonomous delivery, including direct stakeholder engagement. Databricks Certified Data Engineer Associate (minimum). Desirable Databricks Certified Data Engineer Professional. Microsoft AZ-400: Designing and Implementing Microsoft DevOps Solutions. Multi-environment Azure networking (VNet peering, DNS zone design, NAT Gateway). Migrating or standing up CI/CD pipelines, incl. introducing pipeline templates/standards. Governance and identity patterns (e.g. Entra ID, RBAC scoping). Applying regulatory frameworks (e.g. GDPR) to data platform design. Shared service centre or global delivery model experience, ideally in energy or industrial services.

Location: Multiple Countries Nitka Technologies develops software for customers in the US and Europe and brings together about 300 professionals from Eastern Europe, North and South America, Armenia, Georgia and Kazakhstan. We are looking for an experienced DBA (Databricks) for a long-term project. The customer is a company in California, an industry leader in the sale of tickets to events in Europe and the USA. We offer 100%  remote, full-time work. Main tasks: Manage multiple Databricks workspaces (dev/qa/prod); Configure cluster policies, governance & compliance; Create & maintain unity catalog objects: catalogs, schemas, grants, service principals, external storage etc; Monitor and debug failed / long-running jobs using system tables (job_run_timeline, node_timeline, workflow_run); Troubleshoot cluster crashes, driver OOM, executor failures, memory leaks; Investigate Python / Spark errors, dependency conflicts (PyPI, WHL, Maven) Assist users with cluster/job configuration, notebook errors, unity catalog permissions; Explain platform limitations and best practices to Data engineers; Maintain confluence pages with platform rules & troubleshooting guides; Requirements: Experience in implementation, integration or technical support; Experience with Linux, Bash; Confident SQL skills; Strong experience of working with AWS Infrastructure (ec2, s3, iam, vpc, secret management, sqs); Experience with Python sufficient for writing small scripts or applications; Experience of maintaining Databricks jobs & environments; Experience with REST API/SDK; Understanding of file-based databases (DeltaLake, Parquet, Hive); Understanding of of cluster types & node families; Spoken English at Intermediate level or higher; Would be a plus: Databricks REST API / Databricks SDK; Working with schema evolution, time travel, vacuum, compaction, z-order; Debugging corrupted delta tables (conflicting commits, tombstones, missing checkpoints); Understanding of acid implementation on top of object storage; Spark knowledge (jobs, partitions, queries), experience in Kafka or similar technology, familiarity with Terraform / Gitlab CI; Cost monitoring for platform services and objects; Experience in enterprise Data platforms; Working conditions: Nearshore candidates preferred, with availability to work EST or Pacific Time hours Remote work with no time trackers, flexible working hours Full-time (8 hours/day) Attractive USD compensation Paid vacation, holidays, sick leaves

Location: Multiple Countries Nitka Technologies develops software for customers in the US and Europe and brings together about 300 professionals from Eastern Europe, North and South America, Armenia, Georgia and Kazakhstan. We are looking for an experienced Platform Administrator (Databricks) for a long-term project. The customer is a company in California, an industry leader in the sale of tickets to events in Europe and the USA. We offer 100%  remote, full-time work. Main tasks: Manage multiple Databricks workspaces (dev/qa/prod); Configure cluster policies, governance & compliance; Create & maintain unity catalog objects: catalogs, schemas, grants, service principals, external storage etc; Monitor and debug failed / long-running jobs using system tables (job_run_timeline, node_timeline, workflow_run); Troubleshoot cluster crashes, driver OOM, executor failures, memory leaks; Investigate Python / Spark errors, dependency conflicts (PyPI, WHL, Maven) Assist users with cluster/job configuration, notebook errors, unity catalog permissions; Explain platform limitations and best practices to Data engineers; Maintain confluence pages with platform rules & troubleshooting guides; Requirements: Experience in implementation, integration or technical support; Experience with Linux, Bash; Confident SQL skills; Strong experience of working with AWS Infrastructure (ec2, s3, iam, vpc, secret management, sqs); Experience with Python sufficient for writing small scripts or applications; Experience of maintaining Databricks jobs & environments; Experience with REST API/SDK; Understanding of file-based databases (DeltaLake, Parquet, Hive); Understanding of of cluster types & node families; Spoken English at Intermediate level or higher; Would be a plus: Databricks REST API / Databricks SDK; Working with schema evolution, time travel, vacuum, compaction, z-order; Debugging corrupted delta tables (conflicting commits, tombstones, missing checkpoints); Understanding of acid implementation on top of object storage; Spark knowledge (jobs, partitions, queries), experience in Kafka or similar technology, familiarity with Terraform / Gitlab CI; Cost monitoring for platform services and objects; Experience in enterprise Data platforms; Working conditions: Remote work with no time trackers, flexible working hours Full-time (8 hours/day) Attractive USD compensation Paid vacation, holidays, sick leaves

Location: Abu Dhabi, United Arab Emirates; Dammam, Saudi Arabia; Jeddah, Saudi Arabia; Khobar, Saudi Arabia; Riyadh, Saudi Arabia; Amman, Jordan; Kuwait City, Kuwait; Doha, Qatar Workplace: on-site At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior Full-Stack and AI Engineer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Responsibilities: Design, configure, and manage cloud-based lab environments, including Azure Databricks workspaces, AI coding tools, and development repositories. Develop hands-on technical exercises, starter repositories, and training materials for a 3-day programme. Prepare and validate access requirements, permissions, and technical setups before training delivery. Lead practical workshops covering AI-driven software development, agentic coding, CI/CD, and deployment automation. Deliver hands-on training in data engineering, including Spark, Delta Lake, ETL/ELT pipelines, lakehouse architecture, and data governance. Demonstrate AI platform security, including LLM guardrails, model access control, prompt injection prevention, and production monitoring. Conduct Azure Databricks labs covering workspace configuration, notebooks, Delta tables, pipelines, and model inference. Guide participants through integrating AI capabilities into full-stack applications using Python and TypeScript/JavaScript. Perform live coding, troubleshoot technical issues, and support participants with different experience levels. Facilitate team-based capstone projects involving AI-integrated application development. Collaborate with the AI instructor to coordinate technical sessions and practical exercises. Provide complete lab materials and a post-training delivery report. 5+ years of professional software engineering experience, including full-stack development with Python and TypeScript/JavaScript. Strong hands-on experience integrating LLM APIs and developing production AI applications. Proven production experience with Azure Databricks, including workspace configuration, Delta Lake, jobs, and data pipelines. Experience with AI engineering architecture, model serving, inference APIs, retrieval systems, and model evaluation. Practical knowledge of AI platform security, LLM guardrails, prompt injection prevention, and sensitive data protection. Proficiency with agentic AI coding tools such as Cursor, Claude Code, or GitHub Copilot. Strong experience with CI/CD pipelines, Azure cloud services, and deployment automation. Hands-on data engineering experience with Apache Spark, lakehouse architectures, data governance, access control, and lineage. Experience integrating AI models into full-stack applications. Previous experience delivering technical workshops, bootcamps, or corporate training programmes. Excellent presentation, communication, live-coding, and technical troubleshooting skills. Ability to independently prepare and deliver complex hands-on technical labs. Must be based in the UAE and available for 3 consecutive on-site training days in Abu Dhabi, plus approximately 3 days of remote preparation. Must have no current or previous engagement with the end client. Nice to have: Experience with NVIDIA AI Enterprise or GPU-accelerated AI workloads. Experience delivering technical training or solutions within public-sector or regulated environments. Knowledge of UAE data protection and compliance requirements.

Требования: — Минимум 8 лет в data engineering или смежных ролях — 2–3 года практики с платформой Databricks — Сертификат Databricks Certified Data Engineer Associate или Professional

Core Requirements: — Strong hands-on experience with Databricks, especially Databricks Jobs — Advanced Python skills, writing notebooks daily from ingestion to the gold layer — Solid understanding of medallion architecture and how to define bronze / silver / gold boundaries — Experience working with Delta tables — Experience processing large volumes of PDF documents (100K+ files) — Experience calling LLM endpoints from notebooks and tracking token usage and cost — Experience with Azure cloud — Ability to design and consolidate job orchestration pipelines Nice to Have: — Experience with Neo4j or other graph databases — Experience with healthcare or clinical-research data — Experience building data layers consumed by AI agents What You'll Work On: — Extracting and structuring data from large collections of clinical-research PDFs — Building bronze, silver, and gold layers in Databricks with Python notebooks and Delta tables — Integrating LLM endpoints into data pipelines and monitoring token spend — Building a Neo4j graph alongside Delta tables for agents to query — Preparing gold-layer data for an agentic layer used as an API tool — Consolidating scattered and redundant Databricks job pipelines

Location: Mumbai, India We are EnerMech, a specialist service company that delivers safe, integrated solutions for complex energy projects. For over 50 years, we've been energizing our clients across the world with unrivalled expertise, equipment, and technology that supports the entire asset life-cycle - offshore and on land. We enable progress through our three global business lines: Energy Solutions, Infrastructure & Industrial Solutions, and Lifting Solutions. Within these areas, we offer a wide range of services, including cranes, lifting, fluid power, training, equipment rental, pipeline and subsea, process, and valves - all designed to help our clients optimize performance, enhance reliability, and improve efficiency. With a focus on operational excellence, we deliver value through our customized integrated solutions. This approach reduces risk and enhances efficiencies making us a leading and trusted partner every step of the way. The Role & Responsibilities The role will be responsible for taking technical ownership of key workstreams on EnerMech's Azure Databricks data platform, operating across the full platform stack: data modelling and pipeline development in Databricks, the underlying Azure infrastructure, and the CI/CD, DevOps and DataOps practices that keep the platform reliable, secure and scalable. Working for our Enterprise Business Systems (EBS) function in the Mumbai Shared Service Centre, the role holder operates with a high degree of autonomy, makes and documents architectural decisions, resolves complex platform issues, and is a technical point of contact for the global EBS Team, and business stakeholders. Key reponsibilities will include: Design, build, quality and reliable operation of assigned workstreams on the Azure Databricks data platform, from scoping through to production deployment. Integrity of the medallion data model (bronze/silver/gold) for assigned data domains, ensuring data is modelled, validated, documented and certified for downstream reporting and analytics. Build and optimise Delta tables and materialized views, with attention to performance at scale. Design and implement data quality frameworks (preferably DQX or equivalent), including quarantine/error handling and validation against data contracts. Define job-specific compute configurations appropriate to each workload, balancing performance and cost. Contribute to and troubleshoot Terraform-managed infrastructure (networking, storage, Key Vaults, Managed DevOps Pools, Dev Centers). Own and maintain Azure DevOps build and release pipelines, variable groups/libraries, and repository security, permissions and branch policies. Support environment-level Azure configuration, including subscription-level access, RBAC for user and pipeline (service principal) identities, and Terraform state backend management across multiple storage accounts and environments. Operate autonomously across a workstream, from scoping through to production deployment. Use AI-assisted tooling to support day-to-day development, validating outputs against authoritative sources (architecture decisions, technical leads, documentation) before acting on them. Communicate clearly with technical and non-technical stakeholders, including across time zones with colleagues in the UK, Americas, Middle East and Asia Pacific. The Requirements Essential Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline, or equivalent practical experience. Typically 6+ years in data engineering, including 3+ years hands-on with Azure Databricks in production. Demonstrated ownership of medallion architecture design and data modelling. Implemented data quality frameworks and data contracts in production. Implemented PII protection (masking, tokenisation or access tiering) across environments. Platform engineering experience: diagnosing infrastructure issues, not just consuming platform services. Track record of autonomous delivery, including direct stakeholder engagement. Databricks Certified Data Engineer Associate (minimum). Desirable Databricks Certified Data Engineer Professional. Microsoft AZ-400: Designing and Implementing Microsoft DevOps Solutions. Multi-environment Azure networking (VNet peering, DNS zone design, NAT Gateway). Migrating or standing up CI/CD pipelines, incl. introducing pipeline templates/standards. Governance and identity patterns (e.g. Entra ID, RBAC scoping). Applying regulatory frameworks (e.g. GDPR) to data platform design. Shared service centre or global delivery model experience, ideally in energy or industrial services.

Location: Brisbane, Australia VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 10,000 clients in over 100 countries. If you have a favorite team in the NBA, EPL, or NFL, there's a good chance they use VALD Technologies. Years on from its humble beginnings in Brisbane, Australia, VALD has grown to a team of over 300 team members in over 30 countries, with five offices across four continents. Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD’s suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation. About the role VALD is building the world’s largest musculoskeletal database, with over two billion data points and counting. Using this data, we can help practitioners to objectively assess patients’ progress and make more accurate, data-informed treatment decisions. We are looking for someone who has hybrid experience in data engineering and data analysis to help shape the future of the VALD Data Lakehouse. In this role, you will Serve as a data product owner for business-facing dashboards and insights tools - ensuring they align with stakeholder needs and drive measurable impact. Partner with Commercial, Product, and Customer Success teams to gather requirements, define key metrics and build reliable, trusted datasets that power self-serve analytics and business decisions. Design, develop, and own dashboards that track client engagement, retention, renewals - delivering clear, actionable insights to the Commercial and Customer Success teams. Build and maintain scalable analytics pipelines in Azure Databricks to support client-facing and internal reporting across the commercial function. Apply best practices in analytics engineering and dimensional modelling to create scalable, well-documented data models for use across reporting and forecasting tools. Work with the business to continuously improve data generation processes across key domains including product usage, client health, and commercial performance. What we are looking for Our ideal candidate has: Has a strong passion for improving business outcomes and delivering measurable value through data Brings proven experience as an Analytics Engineer, building trusted, scalable data models on platforms such as Azure Databricks and Azure SQL (or similar) Partners with, and effectively manages stakeholders to translate business questions into clear, actionable data solutions Is highly proficient in Spark SQL, PySpark, and T-SQL (or similar) for transforming and modelling data to support commercial analytics use cases Designs and delivers high-quality semantic models and dashboards (Databricks, Power BI or similar), with a strong focus on metric definition and usability Has deep experience with dimensional (Kimball) data modelling to support analytics at scale Champions data quality, governance, and Master Data Management (MDM) to ensure consistency, accuracy, and trust across data assets Why VALD? You will be working in a fast-paced, dynamic company that has a culture around the belief that anything is possible with hard work, creativity, dedication, and good timing. We have a range of benefits we offer to our team, such as: The opportunity to work in a company that is redefining allied healthcare. Working with a range of high-performing individuals and teams across a range of disciplines. Working with contemporary tooling on industry first applications. Casual work attire. Chefs that prepare you delicious fresh breakfast and lunch. An on-site barista to make your coffee just as you like it. A team gym, masseuse, and access to physiotherapy and exercise physiology services. Diversity & Inclusion Commitment VALD’s best asset is not our technology but our people and culture. A culture of inclusion and diversity is critical to our business. We know diverse teams perform better. It's not a separate initiative – we aim to embed inclusion and diversity in everything we do. We are committed to fostering an inclusive work environment and embracing diversity, including gender, nationality, disability, age, marital/parental status, ethnicity, gender identity, socioeconomic background and sexual orientation. We welcome applications from people from all backgrounds. Apply now We can't wait to meet you and discuss what a career with VALD could look like for you! Successful applicants will be subject to background checks (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results. Salary: Up to $175,000 / year

Location: València, Spain We currently have a vacancy for a Senior Databricks Administrator/Architect fluent in English, to offer his/her services as an expert remotely. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team. Your tasks: Collaborate with Data Platforms and Integration team in architecting and implementing scalable enterprise data platform solutions utilizing Azure Databricks, Delta Lake, Unity Catalog, Azure Data Lake Storage Gen2, Azure Data Factory, Azure Event Hub, Azure SQL, and related Azure services; Design and develop enterprise data engineering frameworks supporting batch,  streaming, ELT/ETL, and real-time analytics workloads; Administer and maintain Azure Databricks workspaces including cluster configuration, job scheduling, workspace administration, Unity Catalog implementation, secret management, compute policies, cluster policies, and workspace governance; Define and implement enterprise security architecture including identity integration with Microsoft Entra ID (Azure AD), Role-Based Access Control (RBAC), Privileged Identity Management (PIM), data encryption, private networking, managed identities, Key Vault integration, and secure access patterns; Establish enterprise data governance standards utilizing Unity Catalog including data lineage, data quality, metadata management, catalog organization, access policies, and audit capabilities; Deploy and Configure CI/CD pipelines utilizing Azure DevOps and Databricks Asset Bundles (DAB), Infrastructure as Code (Terraform/Bicep where applicable), deployment automation, release management, and environment promotion strategies; Optimize Databricks workloads through performance tuning, Spark optimization, cluster sizing, workload isolation, caching strategies, partitioning, Delta optimization, Photon, and cost optimization best practices; Design enterprise monitoring, logging, operational dashboards, alerting, and platform health monitoring utilizing Azure Monitor, Log Analytics, Application Insights, and Databricks system tables; Develop reusable architecture patterns, reference implementations, development standards, naming conventions, coding standards, operational procedures, and platform documentation; Support migration of legacy enterprise data warehouses, ETL solutions, and reporting platforms to Azure Databricks and modern Lakehouse architecture; Provide technical support and troubleshooting for production incidents related to  Azure Databricks, Spark workloads, data pipelines, and platform infrastructure. Requirements University degree in combined with relevant IT professional experience of 9 years; At least 8 years of experience in designing and implementing enterprise data platforms; At least 5 years of hands-on experience hands-on Azure Databricks experience in enterprise environments; Experience with architecting modern Lakehouse solutions using Azure Databricks and Delta Lake; Experience in administering Azure Databricks workspaces, clusters, Unity Catalog, compute policies, job orchestration, and workspace security; Experience in developing data engineering solutions using Apache Spark (PySpark and/or Spark SQL); Experience in implementing enterprise data governance utilizing Unity Catalog,  metadata management, data lineage, and fine-grained access controls; Experience implementing Infrastructure as Code using Terraform and/or Bicep; Strong experience implementing CI/CD pipelines utilizing Azure DevOps, automated testing, release management, and deployment automation; Experience designing and working with enterprise security architectures including RBAC, Managed Identities, Private Endpoints, Key Vault integration, encryption, and network security; Experience implementing enterprise data quality frameworks, monitoring, observability, and operational dashboards; Strong understanding of data modelling techniques including dimensional modelling, Data Vault, medallion architecture, and enterprise data warehouse concepts; Strong knowledge of Azure Data Lake Storage Gen2, Azure Data Factory, Azure Event Hub, Azure SQL Database, Azure Key Vault, Azure Monitor, Microsoft Entra ID (Azure AD), and Azure networking; Strong SQL programming skills and proficiency in Python and PySpark development; Knowledge of AI/ML workloads, Databricks ML, Feature Store, Model Serving, and Generative AI architectures is considered an asset; Experience with Power BI, Microsoft Fabric, Synapse Analytics, or other enterprise analytics platforms is highly desirable; Experience working within large international organizations, NGOs, or United Nations agencies is desirable; The following certifications are desirable: Databricks Certified Platform, Architecture/Microsoft Azure Solution Architecture Expert/Databricks, Certified Data Engineer Associate/Professional; Excellent command of the English language. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference (20199/11/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 250 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorise ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

Задачи: — Проектировать и создавать AI-агентов и решения на базе больших языковых моделей (LLM) — Разрабатывать конвейеры данных и lakehouse-решения в Databricks — Интегрировать AI-агентов с Databricks и другими платформами данных — Создавать решения на Python для сбора данных, веб-скрапинга и индексирования контента — Вносить вклад в архитектуру и технические решения — Тесно сотрудничать с международной инженерной командой Требования: — Опыт работы на уровне senior в области разработки ПО или AI-инженерии — Уверенное владение Python — Практический опыт работы с GenAI, LLM и Agentic AI — Опыт работы с инженерией данных и конвейерами данных — Практический опыт работы с Databricks — Способность брать ответственность и участвовать в архитектурных решениях — Владение английским языком на уровне C1 Будет плюсом: — Знание графов знаний и онтологий — Опыт веб-скрапинга — Знание Databricks Genie — Опыт работы с агентскими фреймворками и разработкой с нуля архитектуры Условия: — Медицинская страховка — Более 21 дня отпуска — Возможности профессионального развития — Поддержка карьерного коуча Проект международный, европейское сотрудничество, локация Ташкент, Узбекистан.

Location: Remote (USA) At Livefront, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like CVS, Samsung, General Mills, and Optum create experiences that have reached millions of people, and startups like HomeSpotter and Credly build entirely new businesses that challenge their industries’ status quo. We're looking for an outstanding Senior Databricks Data Engineer to join our growing data practice — someone who builds the data and AI foundations that digital products and intelligent experiences run on. Who you are You are a Databricks-focused Data Engineer who understands that great data platforms are only as valuable as the products, AI workflows, and experiences they enable. You bring deep, production-grade expertise across the Databricks platform and know how to connect platform capabilities to real business outcomes. You thrive in ambiguity and can quickly assess a client's data landscape to recommend and implement the right solutions. You understand that in consulting, your Databricks depth is most valuable when it connects platform capabilities to the products and experiences clients actually use — and you're as comfortable in a product design conversation as you are building a DLT pipeline. You excel at translating complex data challenges into clear technical requirements and can confidently navigate conversations with everyone from data scientists to executives. Your engineering principles are mature and grounded in real-world experience across various industries and scales. You have an interest in and a curiosity about data platforms and the latest advances in data technology. What you will be doing Design and build production data pipelines using Lakeflow Declarative Pipelines, Autoloader, and Structured Streaming, with end-to-end ownership of ingestion, transformation, data quality expectations, and CI/CD deployment via Declarative Automation Bundles. Architect and implement Lakehouse solutions on Databricks — medallion architecture, Delta Lake, Unity Catalog — tailored to the client's analytics, AI, and application needs. Build and maintain Databricks transformation layers — DLT pipelines, PySpark notebooks, and dbt — with data quality constraints and SLAs baked in. Design and maintain the data and AI foundations — Unity Catalog, Feature Store, MLflow, and Model Serving — that power production ML, agent workflows, and AI-enabled digital products. Collaborate with product and backend engineers to design data models, APIs, and application data contracts — ensuring the platform serves the product, not just the warehouse. Consult with clients to understand their data challenges, develop data strategies, and implement sustainable solutions. Adapt your approach based on project needs — sometimes leading data architecture discussions with clients, other times supporting internal teams with specialized data expertise. Work within multi-cloud environments — primarily AWS and Azure — anchoring data platform recommendations around Databricks where it fits the client's architecture and goals. Champion data governance through Unity Catalog — access control, lineage, data quality policies, and compliance — as a first-class part of every engagement, not an afterthought. Design data-to-application architectures — including Lakebase-backed services and Databricks Apps — that connect governed data to AI workflows, digital products, and user-facing experiences. Help build Livefront's Databricks practice — contributing to accelerators, internal enablement, certification goals, and Databricks partner go-to-market materials alongside delivery work. Why you should apply You want to work with passionate and talented people who are always looking for ways to make things better. You desire a work environment where respect, mutual trust, and egoless collaboration are paramount. You want colleagues who take their work seriously but not themselves, and who know how to let loose and have a good time. You like being part of a team with a reputation for excellence that gives back to the community by educating, mentoring, and sponsoring. You want to work on products and accounts that have outsized impact and reach. You believe in sweating the details, giving a damn about quality, and taking pride in going the extra mile. You want to help build a data practice specialization from the ground up — shaping how we go to market with Databricks, what we build as accelerators, and what it means to do this kind of work at a digital product company. What you bring to the table 7-10 years of data engineering experience with at least 5 years in production Databricks environments, preferably in a consulting or client delivery context. Solid working knowledge of AWS and Azure cloud services relevant to Databricks deployments — storage, networking, IAM, and compute — with GCP familiarity a plus. Deep, production-grade Databricks expertise: Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Lakeflow Jobs, Unity Catalog (including fine-grained access control and lineage) — demonstrated through shipped production workloads, not prototypes. Proven experience designing Lakehouse architectures — medallion patterns, Delta Lake table design, partitioning, Z-ordering, and query optimization — at production scale. Hands-on experience with data pipeline testing, observability, and CI/CD for data — including unit testing, data quality frameworks, and version-controlled deployments via Git and Declarative Automation Bundles. Strong proficiency in SQL and Python, with the ability to write clean, performant, and maintainable code. Understanding of data modeling, schema design, and query optimization. Excellent communication skills with the ability to explain complex data concepts to both technical and non-technical stakeholders. Strong problem-solving skills with the ability to navigate ambiguous requirements and deliver pragmatic solutions. Above-average discipline and personal organization skills. Obvious comfort with critique and peer review in the context of an iterative development process. A demonstrated hunger for personal and professional growth. A self-evident love and care for the craft of data engineering. Bonus points if you… Have worked with real-time streaming technologies (Kafka, Kinesis, etc.). Have hands-on experience with alternative cloud data platforms — useful context for migrations and competitive assessments, though Databricks is our primary platform focus. Have experience in healthcare or fintech domains. Have hands-on experience with MLOps or LLMOps on Databricks — MLflow experiment tracking, model registry, Model Serving endpoints, or Vector Search for RAG pipelines. Have experience with Java, Go, or Scala. Have strong illustration skills for technical diagramming and data architecture documentation. Speak, write, and/or educate publicly about data engineering topics. Have contributed to open-source data projects. Hold or are actively pursuing a Databricks certification (Data Engineer Associate or Professional, or Apache Spark Developer) — we treat these as meaningful signals of platform depth, and they directly support our Databricks partner growth goals. Have experience with Databricks Apps, or Lakebase — early familiarity with where the Databricks platform is heading is a strong differentiator. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn, etc). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Compensation is $150,000 - $180,000 Additional information We go out of our way to evaluate all employees and job applicants equally based on merit, competence, and qualifications. We encourage candidates from all backgrounds to apply and consider all qualified applicants. Don't worry, every application will be reviewed by a human.

Location: Remote (Peru) At Livefront, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like CVS, Samsung, General Mills, and Optum create experiences that have reached millions of people, and startups like HomeSpotter and Credly build entirely new businesses that challenge their industries’ status quo. We're looking for an outstanding Senior Databricks Data Engineer to join our growing data practice — someone who builds the data and AI foundations that digital products and intelligent experiences run on. This is a senior-level position with the opportunity to work remotely in Peru. Who you are You are a Databricks-focused Data Engineer who understands that great data platforms are only as valuable as the products, AI workflows, and experiences they enable. You bring deep, production-grade expertise across the Databricks platform and know how to connect platform capabilities to real business outcomes. You thrive in ambiguity and can quickly assess a client's data landscape to recommend and implement the right solutions. You understand that in consulting, your Databricks depth is most valuable when it connects platform capabilities to the products and experiences clients actually use — and you're as comfortable in a product design conversation as you are building a DLT pipeline. You excel at translating complex data challenges into clear technical requirements and can confidently navigate conversations with everyone from data scientists to executives. Your engineering principles are mature and grounded in real-world experience across various industries and scales. You have an interest in and a curiosity about data platforms and the latest advances in data technology. What you will be doing Design and build production data pipelines using Lakeflow Declarative Pipelines, Autoloader, and Structured Streaming, with end-to-end ownership of ingestion, transformation, data quality expectations, and CI/CD deployment via Declarative Automation Bundles. Architect and implement Lakehouse solutions on Databricks — medallion architecture, Delta Lake, Unity Catalog — tailored to the client's analytics, AI, and application needs. Build and maintain Databricks transformation layers — DLT pipelines, PySpark notebooks, and dbt — with data quality constraints and SLAs baked in. Design and maintain the data and AI foundations — Unity Catalog, Feature Store, MLflow, and Model Serving — that power production ML, agent workflows, and AI-enabled digital products. Collaborate with product and backend engineers to design data models, APIs, and application data contracts — ensuring the platform serves the product, not just the warehouse. Consult with clients to understand their data challenges, develop data strategies, and implement sustainable solutions. Adapt your approach based on project needs — sometimes leading data architecture discussions with clients, other times supporting internal teams with specialized data expertise. Work within multi-cloud environments — primarily AWS and Azure — anchoring data platform recommendations around Databricks where it fits the client's architecture and goals. Champion data governance through Unity Catalog — access control, lineage, data quality policies, and compliance — as a first-class part of every engagement, not an afterthought. Design data-to-application architectures — including Lakebase-backed services and Databricks Apps — that connect governed data to AI workflows, digital products, and user-facing experiences. Help build Livefront's Databricks practice — contributing to accelerators, internal enablement, certification goals, and Databricks partner go-to-market materials alongside delivery work. Why you should apply You want to work with passionate and talented people who are always looking for ways to make things better. You desire a work environment where respect, mutual trust, and egoless collaboration are paramount. You want colleagues who take their work seriously but not themselves, and who know how to let loose and have a good time. You like being part of a team with a reputation for excellence that gives back to the community by educating, mentoring, and sponsoring. You want to work on products and accounts that have outsized impact and reach. You believe in sweating the details, giving a damn about quality, and taking pride in going the extra mile. You want to help build a data practice specialization from the ground up — shaping how we go to market with Databricks, what we build as accelerators, and what it means to do this kind of work at a digital product company. What you bring to the table 5-8+ years of data engineering experience with at least 4 years in production Databricks environments, preferably in a consulting or client delivery context. Solid working knowledge of AWS and Azure cloud services relevant to Databricks deployments — storage, networking, IAM, and compute — with GCP familiarity a plus. Deep, production-grade Databricks expertise: Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Lakeflow Jobs, Unity Catalog (including fine-grained access control and lineage) — demonstrated through shipped production workloads, not prototypes. Proven experience designing Lakehouse architectures — medallion patterns, Delta Lake table design, partitioning, Z-ordering, and query optimization — at production scale. Hands-on experience with data pipeline testing, observability, and CI/CD for data — including unit testing, data quality frameworks, and version-controlled deployments via Git and Declarative Automation Bundles. Strong proficiency in SQL and Python, with the ability to write clean, performant, and maintainable code. Understanding of data modeling, schema design, and query optimization. Excellent communication skills with the ability to explain complex data concepts to both technical and non-technical stakeholders. Strong problem-solving skills with the ability to navigate ambiguous requirements and deliver pragmatic solutions. Above-average discipline and personal organization skills. Obvious comfort with critique and peer review in the context of an iterative development process. A demonstrated hunger for personal and professional growth. A self-evident love and care for the craft of data engineering. Bonus points if you… Have worked with real-time streaming technologies (Kafka, Kinesis, etc.). Have hands-on experience with alternative cloud data platforms — useful context for migrations and competitive assessments, though Databricks is our primary platform focus. Have experience in healthcare or fintech domains. Have hands-on experience with MLOps or LLMOps on Databricks — MLflow experiment tracking, model registry, Model Serving endpoints, or Vector Search for RAG pipelines. Have experience with Java, Go, or Scala. Have strong illustration skills for technical diagramming and data architecture documentation. Speak, write, and/or educate publicly about data engineering topics. Have contributed to open-source data projects. Hold or are actively pursuing a Databricks certification (Data Engineer Associate or Professional, or Apache Spark Developer) — we treat these as meaningful signals of platform depth, and they directly support our Databricks partner growth goals. Have experience with Databricks Apps, or Lakebase — early familiarity with where the Databricks platform is heading is a strong differentiator. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn, etc). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Additional information We go out of our way to evaluate all employees and job applicants equally based on merit, competence, and qualifications. We encourage candidates from all backgrounds to apply and consider all qualified applicants. Don't worry, every application will be reviewed by a human.

Location: Colombia; Ukraine; Poland; Brazil; Argentina; Georgia Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are seeking a highly skilled and consultative Senior Data Engineer with Databricks expertise to join our team. What you'll do As a Data Engineer, you will provide technical leadership and guide customers to successful implementations of big data projects, ranging from architecture and design to data engineering to model deployment. You will lead clients through migrations and architect solutions from concept to production. You will provide structured mentorship for other team members and technical support for pre-sales efforts. What you bring - Experience leading design and end-to-end development of distributed Databricks-based solutions, including Lakehouse architectures, ETL pipelines, streaming and batch processing, and integration with client's cloud and on-premises enterprise systems. - Hands-on experience in building big data pipelines. - Hands-on programming experience in Python. - Expert knowledge of SQL, Spark (or PySpark), including data ingestion from a variety of sources such as APIs, relational databases, etc. - Hands-on experience using dbt within Databricks ecosystem. - Solid understanding of data governance, security, and compliance. - Hands-on experience with platform optimization: cluster configuration, partitioning strategies, caching, autoscaling, and job orchestration. - Ability to clearly articulate core Databricks concepts and explain their practical applications. - Bachelor's degree in computer science, Information Systems, Engineering, or equivalent work experience. - Databricks Certification (highly desirable) Nice-to-have - Experience with DevOps using Terraform. - Experience with design and deployment of scalable machine learning pipelines on Databricks using MLflow and Delta Lake. - Experience with Azure, AWS or GCP Databricks deployment. - Experience with Databricks deployments for government clients. - Experience with development of interactive dashboards and reports using BI tools, such as Power BI. - Programming experience with Scala. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems (e.g., lab systems, MES, clinical supply, quality systems, external partners). Create and optimize data flows for structured and unstructured data using Python (PySpark), R, SQL, Databricks, Snowflake, and other modern engineering tools. Develop and maintain specific data repositories, implementing enterprise‑level data models, and creating new models as needed. Enable AI/ML readiness by ensuring data is well‑structured, versioned, traceable, and semantically aligned with enterprise data standards. What we expect : Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred. 6+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment. Proficiency with Python, R, SQL, and cloud-based architectures (AWS services, Snowflake, Databricks, Redshift) along with Spark and dbt. Proficiency in RDS Expertise in ETL and DWH. Experience with NoSQL and graph databases. English language proficiency of B2+ Strong analytical, problem‑solving, and stakeholder‑management skills, with the ability to translate discussions into actionable requirements. Ability to drive multiple exciting projects simultaneously with strong organizational skills and adaptability. Nice to have : Experience working with the histopathology domain Experience with regulated or standards‑driven data environments, such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards. Familiarity with high‑dimensional data (e.g., imaging, sensor data, etc). Experience with principles connecting to or feeding MLOps and model deployment workflows. Knowledge of manufacturing systems (MES), laboratory information systems, or industrial data systems. Exposure to knowledge graph or ontology‑driven architectures. We offer : Competitive compensation Fully remote work Flexible working hours Continuous education, mentoring, and professional development programs A team with an excellent tech expertise

The role involves joining an international project to develop, manage, and automate Azure cloud infrastructure supporting a critical SAP production environment. Key duties include designing and maintaining Infrastructure as Code (IaC) solutions, optimizing CI/CD pipelines with Azure DevOps or GitHub, and managing Azure IaaS and PaaS services such as Virtual Machines, Storage Accounts, Key Vault, AKS, Databricks, and Application Gateway. The engineer will handle containerized applications and Kubernetes clusters, automate infrastructure using Terraform, PowerShell, Shell scripting, YAML, and Python, and enforce automated security controls for IaC. Responsibilities also cover configuring monitoring, logging, and alerting systems to ensure infrastructure reliability, independently resolving incidents and performance issues, and collaborating with cloud engineering and DevOps teams to maintain a secure and efficient SAP environment. Candidates must have strong practical experience with Azure cloud services, IaC, CI/CD pipelines, container technologies, and infrastructure automation, along with skills in troubleshooting complex environments and supporting SAP production systems. Proficiency in English at B2 or higher and availability for on-site work in Eindhoven, Netherlands, are required. Preference is given to those who can provide a team of Azure Cloud Engineers or have experience with large-scale enterprise cloud projects.