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Location: San Francisco, CA, USA About the Role As a Tech Lead Manager on Chime's Data Intelligence Platform, leading the Data Integration Platform team, you will own the group that builds and operates the platform and infrastructure for the ingress and egress of first-party and third-party data into and out of Chime's ecosystem. Your team will be responsible for building and operating reliable, scalable, and secure integration pipelines and connectors that move data between Chime's internal systems and external partners, vendors, and data providers, powering analytics, experimentation, and AI-driven product experiences across Chime. You'll partner closely with other Data Intelligence Platform squads as well as Product Engineering, Security, and Analytics teams to define integration patterns, data contracts, and SLAs that govern how data enters and leaves Chime, supporting both high-scale batch workloads and latency-sensitive real-time flows. Your leadership will directly impact how Chime ingests, exchanges, and delivers data - enabling trusted, self-serve, AI-ready data for Chimers across the company. Chime’s data integration platform is entering its next phase. As our data ecosystem grows, we have a significant opportunity to simplify and standardize how data moves across streaming, batch, and third-party integrations. You will lead the evolution toward a unified, secure, and reliable data conveyance platform while helping advance Chime’s lakehouse architecture. This is a manager-first, hands-on player-coach role. Your primary responsibility is leading and developing the team - setting direction and priorities, coaching engineers, and owning delivery and operational health. You will also remain technically engaged through high-leverage problems: shaping architecture, guiding designs, reviewing critical changes, and writing production code where it unlocks the team’s progress. In this role, you can expect to Own the strategy and roadmap for Chime's Data Integration Platform, including ingestion pipelines, connectors, and the infrastructure that moves first-party and third-party data into and out of Chime's ecosystem. Stay hands-on through architecture, design and code reviews, and targeted production contributions focused on the highest-leverage platform problems, while coaching engineers and owning team execution. Design and evolve scalable, high-performance integration architecture that balances reliability, cost, and ease of use for both analytical and in-product data flows. Build and operate reliable connectors and pipelines for diverse sources and sinks across APIs, event streams, file transfers, and change-data-capture. Ensure performant and secure data movement by defining ingress/egress patterns, throughput and latency targets, schema evolution, and error handling / replay for key data flows. Collaborate across the Data Intelligence Platform and partner teams to define clear data contracts, schemas, and SLAs between producers, the integration layer, and consumers including external partners. Build tooling and automation for governance and compliance across sources and sinks (e.g., RBAC, PII protection, tokenization, lineage, and auditability), with particular attention to data leaving Chime's boundary, in partnership with Security, Risk, and Compliance. Manage and grow a team of engineers, setting clear expectations, providing coaching and feedback, and raising the bar on engineering quality and operational excellence. Establish strong operational practices, including on-call, incident management, postmortems, and SLOs for the integration pipelines and connectors your team owns. Stay ahead of industry trends in data integration, streaming, and ingestion/egress tooling, and thoughtfully introduce technologies that improve our platform's capabilities. To thrive in this role, you Have 8+ years of experience in high-scale, high-reliability software development, with a focus on platforms, infrastructure, and data integration or data movement systems. Have 3+ years of experience managing engineering teams, including hiring, performance management, and developing engineers. Bring hands-on coding ability and a genuine desire to remain technical while leading a team. You are comfortable writing and reviewing production code, particularly where it resolves ambiguity or unlocks the team’s progress Have a track record of scaling products, platforms, and operations to support rapid growth in data volume, complexity, and criticality. Bring deep experience with data integration and movement components, such as ingestion and CDC pipelines, connector frameworks, event streaming, and API- and file-based (e.g., SFTP) data exchange alongside the data lakes/lakehouses (e.g., Iceberg) and warehouses (e.g., Snowflake) they feed and drain. Have proven expertise in system and data architecture for scalable, secure, and cost-efficient data platforms, including schema design, data contracts, and schema-evolution strategies across system boundaries. Are comfortable working with modern data and infrastructure technologies, such as Kafka, Flink, Spark, Airflow, Kubernetes, and connector/ingestion tooling (e.g., Debezium, Fivetran/Airbyte-style frameworks). Are hands-on proficient in Python (preferred) or a comparable language (e.g., Java, Scala), able to write, review, and ship production-quality code, and are fluent in SQL and performance tuning for analytical workloads. Have extensive experience in cloud-based data ecosystems, such as AWS (S3, DynamoDB, Redshift, Snowflake, EMR), GCP (BigQuery, Dataflow), or Azure equivalents. Understand data governance, security, and compliance best practices (e.g., RBAC, PII handling, auditability) especially for third-party data sharing and data crossing Chime's trust boundary and have helped design systems that meet regulatory and internal standards. Are deeply interested in the transformative potential of advanced AI systems and how to build AI-ready data foundations (metadata, lineage, semantic layers, and reliable data pipelines that feed them). Excel at building strong relationships with stakeholders across engineering, product, analytics, security, and finance, as well as external partners and vendors, and can translate between technical and business contexts. Demonstrate strong people leadership, with a track record of building a culture of belonging and engineering excellence. #LI-DA1 #LI-Onsite Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $199,000 — $275,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

Location: UAE - Dubai Workplace: onsite 1inch is the DeFi ecosystem building financial freedom for everyone. 1inch products help users and builders trade, hold and track digital assets - with the self-custody, comprehensive security and the intuitive user experience they need to unlock the potential of true crypto ownership. 1inch protocols and APIs provide core infrastructure across the DeFi industry and beyond. So if you're someone who thinks big, moves fast and wants to make an impact right from day one, then get ready to join our industry-changing team. Your mission As Data & Analytics Lead, your mission is to turn complex business and product questions into reliable, actionable answers. You will combine AI, data analytics, data engineering, and deep DeFi expertise to build a more intelligent and scalable approach to decision-making. You will use AI not just to accelerate existing analytics, but to rethink how we explore data, test hypotheses, identify patterns, and make insights accessible across the organization. You will be highly hands-on, with expert-level Dune capabilities and a strong understanding of DEXes, DEX aggregators, on-chain data, liquidity, routing, and market dynamics. What you’ll do Shape and build a self-service data and AI platform that enables teams to ask better questions, find better answers, and make better decisions. Create intuitive ways for teams to explore trusted data using AI, natural language, dashboards, and other analytical interfaces. Build AI-enabled workflows and agents that accelerate analysis, uncover insights, and reduce repetitive analytical work, ensuring AI-generated answers are grounded in trusted data, transparent, and verifiable. Turn complex and ambiguous business and product questions into structured analyses, clear insights, and actionable answers. Develop metrics and analytical frameworks that connect user behavior, product performance, on-chain activity, market dynamics, and business outcomes. Proactively identify trends, anomalies, opportunities, and risks, and establish standards for analytical quality, metrics, dashboards, and decision support. Design and evolve data architecture, models, pipelines, and transformations, integrating on-chain and off-chain data into reliable, scalable, and reusable data products. Ensure data is accurate, well-structured, documented, discoverable, and accessible to people and AI systems, with strong standards for quality, observability, maintainability, and performance. Use Dune at an expert level to investigate DEX aggregators, DEXes, swaps, liquidity, routing, users, protocols, and markets, building reusable on-chain datasets and analytical models. Combine blockchain, product, and business data to create a comprehensive view of users, ecosystem activity, and market dynamics, and continuously explore new data sources and analytical approaches. Who you are Deep understanding of DeFi and blockchain data, particularly DEXes and DEX aggregators, including swaps, liquidity, routing, transactions, events, traces, and smart-contract interactions. Expert-level Dune skills, with advanced SQL proficiency and demonstrated experience building sophisticated on-chain queries, datasets, dashboards, and analyses. Strong AI-native way of working, with advanced hands-on experience using Cursor to accelerate analytics and engineering, automate workflows, and build AI-enabled data solutions. Strong proficiency in Python for data analysis, data processing, automation, and AI-enabled workflows. Hands-on experience building and operating modern data platforms with ClickHouse and Airflow, including data modeling, pipelines, transformations, data quality, and observability. Proven ability to turn ambiguous business and product questions into structured hypotheses, robust analyses, and clear, actionable answers. Nice to haves Experience working directly within a DEX, DEX aggregator, DeFi protocol, or other data-intensive Web3 product. Experience working with raw multi-chain blockchain data, including decoding contracts, events, traces, and transactions. Experience applying statistical methods, experimentation, forecasting, or anomaly detection to product and business questions. A strong public track record in the DeFi data ecosystem, such as high-quality Dune dashboards, research, open-source contributions, or community analytics.

Location: Lithuania Workplace: fully About the Client Our client is a provider of online payment processing solutions, focusing on a range of services including payment gateway services, global payment processing, and open banking. They serve online businesses across various sectors, supporting multiple currencies and payment methods. Role Overview As a Data Engineer , you will have the opportunity to work with cutting-edge technologies and make a significant impact on data processes within the fintech sector. This role involves developing scalable data pipelines, optimizing data infrastructure, and collaborating with cross-functional teams to ensure data accuracy and quality. Key Responsibilities Work with various data sources and integrate them into internal systems. Develop, optimize, and maintain ETL pipelines and data ingestion processes. Take ownership of data lakes, including their maintenance and documentation. Transform complex data structures into machine-readable formats. Design and maintain databases and data infrastructure. Work closely with other departments to verify the relevance, quality, and accuracy of data. Identify opportunities to improve the reliability and efficiency of existing data processes. Requirements Strong proficiency in Python and advanced SQL. Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions. Strong experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration. Practical experience with Apache Spark for large-scale data processing. Experience with Apache Kafka and event-driven/streaming data pipelines. Hands-on experience with database design, data modeling, optimization, and performance tuning. Practical experience with AWS cloud services and cloud-based data infrastructure. Experience with Apache Airflow for workflow orchestration and scheduling. Practical experience with Docker and containerized environments. Strong knowledge of Git and modern software development workflows. Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices. Ability to write clean, efficient, testable, and maintainable code. Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail. Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment. Languages: English, Russian Experience in fintech Key Soft Skills Strong analytical and problem-solving skills with excellent attention to detail. Ownership mindset, proactivity, and ability to work independently and manage priorities. Strong communication and collaboration skills with the ability to work effectively across teams. What We Offer Competitive salary aligned with experience Collaborative and transparent team culture High-impact role in a scaling fintech company Recognition of personal milestones and achievements Social benefits

Location: Serbia Workplace: fully About the Client Our client is a provider of online payment processing solutions, focusing on a range of services including payment gateway services, global payment processing, and open banking. They serve online businesses across various sectors, supporting multiple currencies and payment methods. Role Overview As a Data Engineer , you will have the opportunity to work with cutting-edge technologies and make a significant impact on data processes within the fintech sector. This role involves developing scalable data pipelines, optimizing data infrastructure, and collaborating with cross-functional teams to ensure data accuracy and quality. Key Responsibilities Work with various data sources and integrate them into internal systems. Develop, optimize, and maintain ETL pipelines and data ingestion processes. Take ownership of data lakes, including their maintenance and documentation. Transform complex data structures into machine-readable formats. Design and maintain databases and data infrastructure. Work closely with other departments to verify the relevance, quality, and accuracy of data. Identify opportunities to improve the reliability and efficiency of existing data processes. Requirements Strong proficiency in Python and advanced SQL. Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions. Strong experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration. Practical experience with Apache Spark for large-scale data processing. Experience with Apache Kafka and event-driven/streaming data pipelines. Hands-on experience with database design, data modeling, optimization, and performance tuning. Practical experience with AWS cloud services and cloud-based data infrastructure. Experience with Apache Airflow for workflow orchestration and scheduling. Practical experience with Docker and containerized environments. Strong knowledge of Git and modern software development workflows. Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices. Ability to write clean, efficient, testable, and maintainable code. Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail. Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment. Languages: English, Russian Experience in fintech Key Soft Skills Strong analytical and problem-solving skills with excellent attention to detail. Ownership mindset, proactivity, and ability to work independently and manage priorities. Strong communication and collaboration skills with the ability to work effectively across teams. What We Offer Competitive salary aligned with experience Collaborative and transparent team culture High-impact role in a scaling fintech company Recognition of personal milestones and achievements Social benefits

Location: Portugal Workplace: fully About the Client Our client is a provider of online payment processing solutions, focusing on a range of services including payment gateway services, global payment processing, and open banking. They serve online businesses across various sectors, supporting multiple currencies and payment methods. Role Overview As a Data Engineer , you will have the opportunity to work with cutting-edge technologies and make a significant impact on data processes within the fintech sector. This role involves developing scalable data pipelines, optimizing data infrastructure, and collaborating with cross-functional teams to ensure data accuracy and quality. Key Responsibilities Work with various data sources and integrate them into internal systems. Develop, optimize, and maintain ETL pipelines and data ingestion processes. Take ownership of data lakes, including their maintenance and documentation. Transform complex data structures into machine-readable formats. Design and maintain databases and data infrastructure. Work closely with other departments to verify the relevance, quality, and accuracy of data. Identify opportunities to improve the reliability and efficiency of existing data processes. Requirements Strong proficiency in Python and advanced SQL. Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions. Strong experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration. Practical experience with Apache Spark for large-scale data processing. Experience with Apache Kafka and event-driven/streaming data pipelines. Hands-on experience with database design, data modeling, optimization, and performance tuning. Practical experience with AWS cloud services and cloud-based data infrastructure. Experience with Apache Airflow for workflow orchestration and scheduling. Practical experience with Docker and containerized environments. Strong knowledge of Git and modern software development workflows. Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices. Ability to write clean, efficient, testable, and maintainable code. Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail. Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment. Languages: English, Russian Experience in fintech Key Soft Skills Strong analytical and problem-solving skills with excellent attention to detail. Ownership mindset, proactivity, and ability to work independently and manage priorities. Strong communication and collaboration skills with the ability to work effectively across teams. What We Offer Competitive salary aligned with experience Collaborative and transparent team culture High-impact role in a scaling fintech company Recognition of personal milestones and achievements Social benefits

Location: Poland Workplace: fully About the Client Our client is a provider of online payment processing solutions, focusing on a range of services including payment gateway services, global payment processing, and open banking. They serve online businesses across various sectors, supporting multiple currencies and payment methods. Role Overview As a Data Engineer , you will have the opportunity to work with cutting-edge technologies and make a significant impact on data processes within the fintech sector. This role involves developing scalable data pipelines, optimizing data infrastructure, and collaborating with cross-functional teams to ensure data accuracy and quality. Key Responsibilities Work with various data sources and integrate them into internal systems. Develop, optimize, and maintain ETL pipelines and data ingestion processes. Take ownership of data lakes, including their maintenance and documentation. Transform complex data structures into machine-readable formats. Design and maintain databases and data infrastructure. Work closely with other departments to verify the relevance, quality, and accuracy of data. Identify opportunities to improve the reliability and efficiency of existing data processes. Requirements Strong proficiency in Python and advanced SQL. Hands-on experience designing, building, and maintaining scalable data pipelines and data processing solutions. Strong experience with ETL/ELT processes, including data ingestion, transformation, integration, and orchestration. Practical experience with Apache Spark for large-scale data processing. Experience with Apache Kafka and event-driven/streaming data pipelines. Hands-on experience with database design, data modeling, optimization, and performance tuning. Practical experience with AWS cloud services and cloud-based data infrastructure. Experience with Apache Airflow for workflow orchestration and scheduling. Practical experience with Docker and containerized environments. Strong knowledge of Git and modern software development workflows. Solid understanding of data architecture, data quality, reliability, scalability, and data engineering best practices. Ability to write clean, efficient, testable, and maintainable code. Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail. Ability to work independently, prioritize effectively, and manage multiple tasks in a fast-paced environment. Languages: English, Russian. Experience in fintech. Key Soft Skills Strong analytical and problem-solving skills with excellent attention to detail. Ownership mindset, proactivity, and ability to work independently and manage priorities. Strong communication and collaboration skills with the ability to work effectively across teams. What We Offer Competitive salary aligned with experience Collaborative and transparent team culture High-impact role in a scaling fintech company Recognition of personal milestones and achievements Social benefits

Location: New York City, New York, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. About the Tavily at Nebius In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. Tavily provides the search and intelligence layer that powers AI agents and retrieval systems with trustworthy, real-time information. We work with some of the most innovative teams in AI, from fast-growing startups to global enterprises, helping them build agents that are not only intelligent but informed. About the Role We're looking for a senior, full-stack analyst / data scientist to own Product and PLG analytics end-to-end. You'll own the metrics behind our self-serve motion (signup, activation, usage, conversion, expansion and retention) and find the drivers behind them . You'll work directly with our CEO and leadership as a thought partner on product and growth decisions. This role is fully independent. When a question comes up, you take it all the way: from building the pipeline, model the data, train and deploy the model, analyze the results and come back with a clear recommendation. Nothing waits in a queue for someone else. You'll also work closely with the other analysts on the team, share methods and standards, and collaborate across Product, Engineering, Growth, Marketing and GTM. What You'll Do • Own Product and PLG analytics end-to-end: define, instrument and measure the self-serve funnel, from first API call through activation, conversion to paid, expansion and churn. • Uncover the drivers behind top-level KPIs: which behaviors, use cases and product experiences predict activation, retention and monetization. • Build what you need: data pipelines and models (SQL, dbt, Python, orchestration) that turn raw product, usage and billing data into trusted, reusable datasets. • Build and ship predictive models (conversion propensity, churn risk, usage forecasting, lead and account scoring) and bring their outputs into product and GTM workflows. • Design, run and evaluate experiments (A/B tests, pricing and packaging tests, onboarding changes) and apply causal inference where you can't run a clean experiment. • Proactively monitor key business and product metrics, investigate trends and anomalies, and surface insights stakeholders can act on. • Partner directly with the CEO and leadership on strategic questions, including pricing, growth levers, product bets and market opportunities, and turn ambiguous questions into clear analysis and decisions. • Set the standard for how we measure product success: metric definitions, a shared source of truth and analytical rigor across teams. What We're Looking For (Must-Haves) • 5+ years of experience as a Product / Growth Analyst, Data Scientist or equivalent. • 2+ years in a SaaS company, with deep understanding of funnels, cohorts, activation, retention, monetization and PLG dynamics. • A strong statistical foundation. • A proven record of working end-to-end on your own, from data engineering through modeling to a delivered recommendation. • Strong hands-on experience using Python for data analysis, experimentation, machine learning and data modeling in a production environment. • Comfort working with large, messy, event-level datasets. • Hands-on experience building, validating and deploying predictive models (e.g., classification, forecasting, segmentation) that were used to make real business decisions. • Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders, including executive leadership. • Strong communication: you can turn complex analysis into a clear, compelling story and a concrete recommendation. • Experience with modern data tooling (Snowflake/BigQuery, dbt, Airflow, and BI tools like Omni/Looker/Tableau). • BSc in Statistics / Math / CS or equivalent. Nice to Have • Experience at an API-first, developer-focused or PLG company. • Experience with product analytics platforms (PostHog, Amplitude, Mixpanel). • Experience with pricing and packaging analysis or usage-based billing models. • Familiarity with LLMs / AI tooling, and using AI agents to speed up your own analytical work. • Evidence that you build things on your own: a GitHub profile, portfolio, side projects or publications. • MSc / PhD in Statistics / Math / CS or equivalent. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $179,000 — $224,000 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Задачи: — разрабатывать и доводить до продакшена модели компьютерного зрения; — решать задачи речевой аналитики: транскрибация звонков, диаризация спикеров, извлечение сущностей и интентов, оценка качества коммуникаций и построение аналитических витрин по разговорам; — строить классический ML: скоринг, ранжирование, прогноз конверсии и оттока, рекомендательные и matching-модели на табличных данных; — проводить полный цикл ML: постановка задачи, разметка и подготовка данных, обучение, валидация, A/B и offline-оценка, мониторинг качества в проде; — упаковывать модели в сервисы (API/batch), выкатывать в продакшен, обеспечивать стабильность, latency, отказоустойчивость и версионирование; — настраивать пайплайны обучения и инференса, feature store / датасеты, трекинг экспериментов и CI/CD для ML; — работать с продуктом и бизнесом: формализовать метрики успеха, декомпозировать гипотезы, объяснять решения моделей и влияние на KPI. Требования: — уверенный Python и опыт промышленной разработки, а не только ноутбуков; — практический опыт Computer Vision (классификация, детекция, сегментация) и работы с современными CV-архитектурами; — опыт речевой аналитики / speech-to-text: ASR, диаризация, NLP поверх транскриптов; — сильный классический ML: feature engineering, градиентный бустинг, валидация, работа с дисбалансом и утечками; — опыт вывода ML в прод: сервисы инференса, batch/online, мониторинг дрифта, ретрайн, откат моделей; — понимание MLOps: Docker, оркестрация пайплайнов, трекинг экспериментов, версионирование данных и моделей; — умение читать SQL и работать с витринами/хранилищами; — плюсом — опыт GPU-инференса и оптимизации (ONNX, Triton, квантизация). Условия: — стек: Python, Java, Trino, DBT, Iceberg, Airflow, llama.cpp, LLM, Whisper, FastAPI, MLFlow, S3 + то что принесешь ты.

Требования: — Уверенные знания Linux (Debian/Ubuntu), сетей, контейнеризации; — Опыт развёртывания и эксплуатации продуктовых Kubernetes кластеров; — Опыт работы инструментами автоматизации (ansible, terraform); — Опыт использования GitOps инструментов (FluxCD, ArgoCD); — Опыт работы с системами мониторинга: Grafana, Prometheus, ELK Stack, Sentry; — Понимание процессов и опыт работы с инструментами CI/CD (gitlab ci); — Законченное высшее образование; — Гражданство РФ. Задачи: — Поддержка инфраструктуры развёрнутой на bare metal серверах и vm; — Развёртывание и эксплуатация кластеров Kubernetes; — Администрирование баз данных: Postgresql, Elasticsearch, Redis, Clickhouse; — Администрирование Airflow; — Развёртывание и поддержка инфраструктурных сервисов: Gitlab, Harbor, Vault, etc; — Автоматизация инфраструктуры с использованием ansible, terraform, flux; — Настройка системы мониторинга: VictoriaMetrics, Grafana; — Обеспечение непрерывной работоспособности и доступности сервисов; — Документирование процессов и систем. Условия: — Оформление по ТК РФ; — Работа в команде профессионалов на стыке передовых ИТ и науки; — Работа с Big Data и ML, собственный корпоративный ЦОД; — Возможность профессионального роста, обучение; — График работы 5/2, гибрид, плавающее начало рабочего дня.

Задачи: — Развивать и поддерживать инфраструктуру DWH — Строить и развивать CI/CD-процессы для data и ML-разработки — Разрабатывать и поддерживать пайплайны обработки данных и оркестрации (Airflow) — Реализовывать end-to-end ML-пайплайны: от сбора данных до деплоя и мониторинга моделей — Проектировать и развивать MLOps-платформу (выбор и интеграция инструментов) — Разворачивать и поддерживать инфраструктуру для ML-задач: (JupyterHub + GPU, Airflow, ClickHouse, PostgreSQL, S3 и др.) — Взаимодействовать с ML- и Data-инженерами для вывода решений в production — Настраивать мониторинг и алёртинг: качество данных, стабильность пайплайнов, ресурсы — Автоматизировать рутину и развивать self-service инструменты для data-команды Требования: — Уверенный опыт с Docker и Kubernetes — Опыт работы с Airflow (или аналогами оркестрации) — Практика построения CI/CD для data/ML пайплайнов — Хорошие знания Python, SQL и Git — Опыт развёртывания ML-инфраструктуры (GPU-кластеры, хранилища, orchestration) — Опыт работы с облачными платформами — Понимание принципов CI/CD и автоматизации деплоя — Опыт работы с API и понимание highload-систем — Опыт работы со стримингом данных (Kafka / аналоги) — Практика настройки мониторинга и логирования — Уверенная работа в Linux — Будет плюсом: Опыт внедрения систем управления экспериментами (MLflow, ClearML)

Задачи: – Проектировать витрины данных: модель, гранулярность, состав атрибутов, историчность – Разрабатывать и поддерживать процессы наполнения витрин, подключать новые источники данных – Работать с сотрудниками Банка: выявлять и уточнять требования, разбираться в методологии расчетов, согласовывать результат – Предлагать варианты реализации с оценкой трудоемкости и ограничений, а не только выполнять поставленную задачу – Решать ad-hoc запросы бизнеса: быстро находить данные, объяснять расхождения в цифрах – Разрабатывать отчеты и дашборды – Готовить сопроводительную документацию: описание витрин, регламент расчета показателей Требования: – Опыт работы аналитиком и/или инженером данных от 6 лет, из них от 2-3 лет в Банке обязательно – Экспертное знание SQL: оконные функции, аналитические запросы, сложные соединения – Навыки оптимизации запросов: чтение плана выполнения, работа с большими таблицами, партиционирование, индексы – Опыт работы с промышленными СУБД – Опыт развития хранилища данных: проектирование витрин, разработка ETL/ELT – Опыт работы в банковской сфере или в финансовых организациях – Умение слушать и задавать уточняющие вопросы, говорить с бизнесом на его языке Будет плюсом: – Высшее техническое или экономическое образование – Опыт работы с Airflow, Informatica, FormIT – Опыт разработки дашбордов в BI-инструментах – Знание финансов и бухгалтерского учета, опыт построения отчетности по этим направлениям – Опыт работы с регуляторной отчетностью Условия: • Оформление: ИП • Формат работы: удалённо • Локация: РФ • Уровень дохода: до 400 тр гросс

Задачи и обязанности: — Анализ бизнес-требований и постановка четких технических заданий инженерам данных на разработку и поддержку ETL-пайплайнов. — Валидация данных и приемка работы у инженеров данных, контроль качества. — Анализ отчетности: поиск аномалий, исследование причин отклонений, формирование и проверка гипотез. — Создание автоматизированной отчетности по метрикам. — Проведение AdHoc-исследований по запросам команды маркетинга для поддержки принятия операционных и стратегических решений. — Проектирование и аналитическое сопровождение A/B-тестов для оценки эффективности маркетинговых инициатив. Требования: — Уверенное знание Python и его библиотек для анализа данных. — Продвинутое знание SQL, опыт написания сложных запросов и оптимизации их производительности. — Аналитический склад ума, самостоятельность и проактивность. — Умение декомпозировать сложную бизнес-проблему на измеримые задачи. — Самостоятельность и проактивность, гибкость, умение выявлять бизнес-потребности и собирать/уточнять требования у бизнес-заказчиков. Будет плюсом: — Опыт работы с корпоративными DWH (Greenplum, Clickhouse и др.), инструментами автоматизации (например, Airflow), BI-системами (Tableau, Power BI). — Опыт работы в отделе маркетинга и понимание метрик performance-маркетинга (CPA, CPO, ROMI/ROAS, LTV, CAC). Условия: — Гражданство РФ/РБ и дружественные страны. — Локация: Москва, проспект Лихачёва. — Формат работы: гибрид. — Срок проекта до 30.09.2027 с возможной пролонгацией. — Возраст до 45 лет. — Ставка 2000 рублей с НДС, отсрочка 35 рабочих дней.

Location: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. ABOUT THIS ROLE We are looking for a Senior Data Engineer to join our Data Team and help build reliable, scalable data systems that support analytics, data science, and critical business use cases across Strava. In this role, you will design and operate data pipelines, build high-quality domain data models, improve our dbt and data transformation workflows, and help ensure data is accurate, well-governed, and easy to use. You will also contribute to areas such as data ingestion, data quality, privacy and GDPR workflows, and the ongoing evolution of our data warehouse and data lake. We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office — three days per week. WHAT YOU’LL DO: - Design, build, and operate foundational data systems and shared data assets that serve a broad range of analytical, operational, and business use cases across Strava. - Build and evolve scalable data ingestion and transformation frameworks that move, process, clean, standardize, and organize data across our data lake and data warehouse. - Develop reusable data engineering tools and abstractions that improve how engineers build and operate data pipelines, including frameworks and capabilities around technologies such as dbt. - Design high-quality, durable domain data models — such as user, subscription, activity, or other core business domains — that provide consistent definitions and reusable foundations for teams across the company. - Build systems and workflows that support data governance, privacy, and regulatory requirements, including GDPR-related deletion, retention, access, and data lifecycle management. - Improve the reliability and observability of our data platform through automated testing, data quality checks, lineage, monitoring, alerting, and operational tooling. - Optimize large-scale data processing and storage for performance, maintainability, scalability, and cost across both warehouse and data lake environments. - Partner with data engineers, analytics engineers, software engineers, data scientists, security, privacy, and infrastructure teams to establish scalable data architecture and engineering standards. YOU WILL BE SUCCESSFUL HERE BY: - Thinking beyond individual pipelines and designing reusable systems, abstractions, and data models that solve common problems across multiple teams and use cases. - Building well-defined domain data assets with clear semantics, ownership, lineage, and interfaces so downstream consumers can confidently build on top of them. - Applying strong data modeling principles to represent complex business entities and relationships in ways that are extensible, understandable, and efficient. - Maintaining a high bar for data correctness, reliability, privacy, and operational excellence across critical production data systems. - Making thoughtful engineering tradeoffs across data freshness, scalability, storage, compute cost, complexity, and developer productivity. - Proactively identifying recurring pain points in the data development lifecycle and creating tooling or platform capabilities that eliminate manual work and improve engineering velocity. - Designing data systems with governance and regulatory requirements in mind, rather than treating privacy and compliance as downstream concerns. - Bringing software engineering discipline to data infrastructure through testing, modular design, version control, CI/CD, observability, documentation, and code review. WHAT YOU’LL BRING TO THE TEAM: - You have 3–5+ years of professional experience in Data Engineering, Data Infrastructure, Software Engineering, or a related field, with experience owning production data systems. - You have strong expertise in SQL and data modeling, including experience designing dimensional, normalized, or domain-oriented data models for large-scale analytical systems. - You have experience building and operating ETL/ELT and data processing systems using technologies such as dbt, Airflow, Spark, or similar frameworks. - You have experience developing reusable tooling, frameworks, or abstractions that improve how data pipelines and transformations are built, tested, deployed, or operated. - You are proficient in at least one general-purpose programming language such as Python, Scala, Java, or Go and are comfortable applying software engineering principles to data systems. - You understand modern data warehouse and data lake architectures and have worked with technologies such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or similar systems. - You have experience processing and transforming large datasets, including handling schema evolution, data normalization, deduplication, backfills, incremental processing, and data quality. - You understand data governance and data lifecycle concepts such as lineage, retention, deletion, access control, PII handling, and GDPR/privacy requirements. - You have experience implementing production-grade data quality, monitoring, alerting, testing, and observability for data pipelines and datasets. - You can independently reason about data architecture and make sound technical decisions around modeling, ingestion, transformation, storage, reliability, scalability, and maintainability. - You are comfortable working with cloud infrastructure such as AWS, GCP, or Azure and understand the infrastructure that supports large-scale data processing systems. Experience with Kafka, Flink or other streaming systems; Kubernetes; Iceberg or other open table formats; data catalogs and lineage systems; schema management; CDC; or internal developer platforms for data engineering is a plus. For information on benefits, please click here https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub. WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, 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. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: Athens, Greece We are looking for a Senior Backend Engineer (Python) to join a technically demanding project involving data-intensive processing, system integration, and semantic technologies. You will play a key role in taking ownership of an existing codebase, stabilising it, and evolving it in line with project requirements. This role is ideal for an experienced engineer who is comfortable working with complex systems and understands data-driven architectures . What You'll Do: Analyse, understand, and take ownership of an existing Python-based backend; Refactor and enhance backend components with a focus on maintainability and performance; Implement and maintain data processing pipelines and integration logic; Collaborate closely with data/semantic engineers on RDF/SPARQL-driven workflows; Contribute to architecture reconstruction and technical documentation; Support deployment, configuration, and troubleshooting activities; Ensure code quality through reviews, testing, and best practices. Requirements 3+ years of professional experience in backend development; Strong proficiency in Python; Experience with: Apache Airflow and AWS; Data-intensive or integration-heavy systems; APIs, batch processing, and backend services; Configuration-driven systems (XML / JSON / YAML); Solid understanding of: Software architecture and design patterns; Debugging and working with legacy codebases; Experience working in complex, multi-stakeholder projects (EU or public-sector projects is a plus). Nice-to-Have: Familiarity with Semantic Web technologies (RDF, SPARQL, OWL); Experience with data modelling or knowledge-based systems; Exposure to DevOps practices (CI/CD, containerisation); Experience contributing to or maintaining technical documentation (e.g. AsciiDoc, Antora). Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( SBEP/11/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1200 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, 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 at 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 authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

Задачи: — Разрабатывать и поддерживать программные решения на платформе 1С; — Разрабатывать механизмы интеграции между системами и сервисами (1С и не только); — Покрывать решения автоматизированными тестами (Vanessa-Automation, Gherkin, xUnitFor1C, Vanessa-ADD); — Участвовать в разработке и внедрении CI/CD-процессов; — Сборка релизов и автоматизация процессов развертывания продуктов и сервисов на стендах DEV, UAT, PROD; — Участвовать в настройке мониторинга систем/сервисов; — Выявление причин сбоев и устранение ошибок в работе бизнес-приложений. Требования: — 1С:8.3+ (платформа, кластер, язык), Python, Sonarqube; — MS SQL и/или PostgreSQL; — Apache Airflow, Apache Kafka; — Jenkins; — Docker и/или Kubernetes и/или OpenShift; — Grafana, Prometheus; — Redis, Nginx, ElasticSearch, Logstash, Kibana; — Git, GitLab, другая система контроля версий. Условия: — Гибридный формат работы; — Конкурентная заработная плата; — Профессиональное обучение и развитие; — Добровольное медицинское страхование сотрудника и несовершеннолетних членов семьи, страхование жизни и здоровья.

Задачи: — Разворачивать компоненты в Kubernetes: Helm, операторы, values по контурам/кластерам, квоты, taints, node pools; — Вести GitOps (Argo CD, Flux): состояние контура совпадает с git; — Сопровождать CI моделей и сервисов: Jenkins-пайплайны обучения и инференса, перенос в GitLab CI; — Настраивать MLOps-контур: MLflow и S3/MinIO — реестр и артефакты; Airflow, Argo Workflows, Spark — batch; KServe, Seldon — online и LLM; — Поднимать зависимости: PostgreSQL, Kafka, Redis, OpenSearch, RabbitMQ; — Строить observability: VictoriaMetrics, Grafana, Vector, Kafka, Elasticsearch / Loki / VictoriaLogs, алерты, в том числе по GPU; — Настраивать доступ: Istio, cert-manager, F5, OIDC (Dex, Keycloak); — Закрывать требования ДКБ: RBAC, сервисные аккаунты и ТУЗ, секреты, образы, аудит, разделение контуров; — Разбирать инциденты платформы и доводить модель от артефакта в MLflow до запуска в целевом контуре. Требования: — Самостоятельно выводили компонент в промышленный контур; — Kubernetes: операторы, RBAC, NetworkPolicy, StorageClass, пулы нод, обновление без простоя; — GitOps и CI/CD: чарт, values по средам, сборка, доставка, откат; — Понимание MLOps-цикла: обучение, реестр, артефакты в S3, batch по расписанию, online-serving; — Опыт в банке или контуре с сопоставимым ИБ: несколько сред, согласование изменений, аудит, секреты, разграничение доступа; — Linux, ingress/TLS, диагностика по логам и метрикам. Будет плюсом: — KServe, Seldon, Spark on Kubernetes, GPU в Kubernetes, миграция Jenkins → GitLab CI, Vault/SOPS, Longhorn, требования CIS/ДКБ к контейнерным платформам. Условия: — Стабильный и прозрачный доход: размер заработной платы обсуждается по итогам собеседования; — Работа в agile-команде; — Удаленный формат работы; — Сложные и интересные задачи, современный стек технологий; — Возможность вертикального и горизонтального карьерного роста: регулярно проходят тренинги, вебинары, митапы и демо-дни; — Доступ к бесплатным корпоративным библиотекам Alpina Digital, MyBook и бизнес-изданий; — Предложения от Банка только для сотрудников: собственный спортзал, а также скидки на услуги туристических агентств, продукты питания, в рестораны, бары, магазины.

Задачи: — сопровождать и эксплуатировать Data Lake платформы; — поддерживать S3/Object Storage инфраструктуру; — мониторить, диагностировать и устранять инциденты; — проводить troubleshooting производительности платформы и storage систем; — сопровождать Kubernetes и компоненты Data Lake; — проводить RCA и postmortem analysis; — автоматизировать эксплуатационные задачи; — взаимодействовать с командами Data Engineering и инфраструктуры; — сопровождать Big Data Platform. Требования: — опыт работы в роли DevOps/SRE Engineer от 3-х лет; — опыт работы в FinTech-компаниях; — экспертный опыт администрирования Linux; — опыт сопровождения высоконагруженных distributed systems; — глубокое понимание S3/Object Storage и distributed storage architecture; — опыт сопровождения Kubernetes-платформ; — практический опыт эксплуатации компонентов Data Lake: Apache Spark, Airflow, Flink, Kafka, Apache Iceberg; — опыт эксплуатации MinIO/Object Storage решений; — понимание replication, erasure coding, consistency, fault tolerance; — практический опыт troubleshooting: CPU, RAM, network, disk I/O, latency, throughput; — опыт работы с observability stack: Prometheus, Grafana, alerting, log analysis; — опыт автоматизации: Ansible, Terraform, Bash, Python; — понимание incident/problem management и SRE-практик; — навыки RCA, postmortem analysis и повышения reliability платформ. Условия: — уровень зарплаты обсуждается индивидуально, есть доплаты за менторство и профактивности; — долгосрочные проекты от российских заказчиков, возможность менять направления, прозрачная система Performance Review; — релокейт между офисами, выбор формата работы (удалённо, офис, гибрид), адаптация для новых сотрудников; — доступ к корпоративному порталу, митапам, конференциям (и как гость, и как спикер); — ДМС со стоматологией, частичная компенсация спорта, бесплатный английский, оплачиваемый отпуск и больничные; — тимбилдинги, детские праздники, внутренние мероприятия; — офисы в Москве, Санкт-Петербурге, Казани, Нижнем Новгороде, Самаре.

Задачи: — Настраивать средства CI/CD для команды разработчиков; — Совершенствование CI/CD процессов; — Настраивать средства централизованного сбора и анализа логов для сервисов компании; — Помощь в формировании культуры релиз-менеджмента; — Подготовка сценариев разворачивания приложений и их формальное описание с помощью Jenkins; — Управление конфигурацией серверов; — Совершенствование систем мониторинга и логирования; — Тестирование инфраструктуры web-приложений (и esb-сервисов для направления SIP) до их выхода в продакшн: прогнозирование нагрузки, определение проблемных мест и их оперативное устранение; — Совершенствование системы контейнерной оркестрации; — Решение проблем и инцидентов; — Ведение документации, написание инструкций и схем. Требования: — Высшее техническое образование; — Опыт в банковской сфере; — Опыт работы с любой из систем Continuous Integration (Jenkins, TeamCity, Bamboo & etc); — Опыт работы с любой из систем Continuous Delivery (ArgoCD, Flux & etc); — Опыт работы с системами хранения артефактов (JFrog Artifactory, Nexus, ProGet); — Опыт проектирования и самостоятельной реализации CI-пайплайнов; — Опыт работы с Docker или podman, сборка образов, buildah в k8s; — Опыт работы с Kubernetes; — Опыт работы с Liquibase; — Уверенное владение Git; — Уверенное владение скриптовым языком Bash, GNU coreutils и BusyBox; — Приветствуется навык работы с Ansible и Jinja2; — Приветствуется навык работы с gradle; — Умение тестировать и измерять результаты своей работы; Дополнительные (желательные) требования: — Опыт работы с Service Mesh в части настройки observability, sidecar, канареечных релизов; — Опыт разработки Pipeline для рендеринга документов из Asciidoc; — Опыт работы с API при разработке Pipeline; — Опыт работы с Jira, Confluence, Bitbucket, GoLive, Sonarqube-CE; — Опыт работы с инструментами ETL, Airflow, Spark, Hadoop, JupyterHub, Trino, OpenMetaData; — Опыт работы с системами и протоколами авторизации/аутентификации: Keycloak, Kerberos, OAuth 2.0, OpenID Connect. Условия: — Возможность участия в интересных проектах; — Возможность профессионального и карьерного роста в компании; — Опыт работы в команде профессионалов; — Специальные тарифы для сотрудников в спортивные клубы и языковые курсы и пр.