Data Engineer

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, platform reliability, and cloud-native data infrastructure to improve performance, scalability, and observability of global data ecosystems. Hybrid work model with competitive salary and comprehensive benefits. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend engineering skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience in cloud environments (AWS preferred), Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven or streaming architectures, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable and reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to improve performance and scalability of global data systems. It is a hands-on role working with large-scale data pipelines, streaming, and cloud environments. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills in Python, Java, or Kotlin, Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven architectures or streaming systems, Understanding of end-to-end data flow and data modeling, Experience designing scalable and reliable data systems, Experience with infrastructure automation tools 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to support global, data-intensive applications. The engineer will enhance performance, scalability, and observability of production datastores across a multi-region environment. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Hands-on experience with relational or NoSQL databases, Experience with large-scale data pipelines and data processing systems, Experience with event-driven architectures or streaming/batch processing, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable, high-performance, reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Engineer role in the banking sector focused on building scalable Big Data solutions supporting Financial Crime Prevention processes. The position involves developing distributed data pipelines and streaming applications using Spark and Scala in a Continuous Delivery environment. It is a long-term hybrid project with an immediate start. 🗂️ Requirements: Senior-level experience in Big Data and ETL, Senior-level Scala proficiency, Senior-level Spark and Spark SQL expertise, Strong SQL knowledge, Experience with Data Testing, Practical experience with distributed large-scale data systems 📃 Skills: Scala, Spark, SparkSQL, SQL, ETL, BigData, DataTesting 🏢 Description: 📍 Location: Gdańsk / Gdynia / Warsaw (hybrid) 🚀 Start: ASAP 💶 Rate: 35–45 EUR/h About the role We are looking for a Senior Data Engineer to work on a long-term project for a leading client in the banking industry . In this role, you will implement complex data requirements and build scalable solutions that support the client’s Financial Crime Prevention processes . Responsibilities Build distributed Big Data processing pipelines handling large volumes of structured and unstructured data in near real-time Develop streaming applications connecting multiple internal and external data sources Transform and enrich data with Apache Spark for analytics, visualization, and search Deliver clean, high-quality datasets for downstream systems Work closely with DevOps, QA, and Product teams in a Continuous Delivery environment Requirements Experience with Big Data / ETL / SQL / Data Testing (Senior level) Senior-level Scala Senior-level Spark and Spark SQL Practical experience with distributed, large-scale data systems Recruitment process First interview: Conversation with our Talent Team Technical interview: Discussion with one of our developers Final interview: Meeting with the CTO

🏢 Summary: Senior Python Engineer role focused on building and maintaining production-grade data tooling and pipelines for large-scale, time-series and event-based datasets in a high-demand environment. The position involves optimizing data workflows, ensuring data quality and observability, and working with analytical databases. Onsite employment contract in Wrocław with competitive salary and impact on internal data platforms. 🗂️ Requirements: Minimum 7 years of commercial experience with Python as primary language, Strong hands-on experience with Pandas, NumPy, Polars, Dask or similar Python data tools, Experience working with time-series, event-driven or large historical datasets, Strong SQL skills, Hands-on experience with analytical databases or data platforms (e.g. ClickHouse, Snowflake, BigQuery, Redshift, Databricks, Druid), Experience building production data pipelines, internal tools or reusable Python components, Practical approach to data quality, debugging, monitoring and performance optimisation, English proficiency at C1 level 📃 Skills: Python, Pandas, NumPy, Polars, Dask, SQL, ClickHouse, Snowflake, BigQuery, Redshift, Databricks, Druid 🏢 Description: Senior Python Engineer 📍 Wrocław, Poland | Onsite 📄 Employment contract 💰 Up to 50,000 PLN gross/month We are looking for a Senior Python Engineer to join a team building data tooling, libraries and production pipelines used in a high-scale, technically demanding environment. You will work closely with large historical, time-series and event-based datasets, helping improve how data is processed, validated, monitored and made available to technical teams. What you will work on Building and maintaining production-grade Python tools, libraries and data pipelines Working with large-scale historical, time-series and event-based datasets Improving data quality, validation, observability and monitoring Optimising data-processing workflows and pipeline performance Writing SQL queries and working with analytical databases and data platforms Collaborating with engineers and technical users to improve internal data workflows Solving practical problems around data reliability, scale and performance What we are looking for min. 7 years of commercial experience with Python as your primary programming language Strong hands-on experience with Pandas , NumPy , Polars , Dask or similar Python data tooling Experience working with time-series, event-driven or large historical datasets Strong SQL skills Hands-on experience with analytical databases or data platforms such as ClickHouse , Snowflake , BigQuery , Redshift , Databricks , Druid or similar Experience building production data pipelines, internal tools or reusable Python components A practical approach to data quality, debugging, monitoring and performance optimisation Good English communication skills (C1) What is offered Employment contract Salary up to 50,000 PLN gross per month Onsite work in Wrocław A chance to work on technically challenging, data-heavy problems Real influence on tools and workflows used by experienced technical teams International working environment and collaboration with strong engineering profiles If you enjoy Python, large-scale data and building reliable tools that make other teams more effective, we would be happy to speak with you!

🏢 Summary: Long-term remote contract for a Senior Data Engineer focused on large-scale migration from SQL Server to Databricks/Delta Lake in an enterprise insurance environment. The role involves transforming complex SQL logic into scalable PySpark/Python solutions and developing production-grade data engineering code within Medallion architecture. You will work with petabyte-scale data and contribute to architectural design, code reviews, and CI/CD processes. 🗂️ Requirements: Strong commercial experience in data engineering (Mid/Senior level), Very good practical knowledge of Python, Hands-on experience with PySpark, Commercial experience with Databricks, Experience with Delta Lake, Advanced SQL skills and ability to analyze complex stored procedures, Experience with large shared codebases, Strong OOP knowledge, Application of Clean Code and refactoring principles, Experience in data modeling (transactional and analytical), Understanding of Medallion architecture, Experience with enterprise development workflows, Ability to write production-grade PySpark/Python code 📃 Skills: Python, PySpark, Databricks, DeltaLake, SQL, SQLServer, OOP, CleanCode, Medallion, Azure, DataFactory, Git, CICD, DevOps, PowerBI, Spark 🏢 Description: Be in IT to firma rekrutacyjna, wyspecjalizowana w poszukiwaniu Specjalistów z branży technologii informatycznych. Obecnie, dla naszego klienta, poszukujemy osoby na stanowisko Senior Data Engineer . Zakres obowiązków: Długofalowa współpraca z międzynarodową, topową firmą consultingową, świadcząca usługi IT dla dużych i średnich firm z różnorodnych sektorów jak automotive, healthcare, finanse, bankowość czy produkcja. Wsparcie wielkoskalowej transformacji systemów z SQL Server do platformy Databricks / Delta Lake w środowisku ubezpieczeniowym klienta. Analiza i transformacja złożonej logiki biznesowej (stored procedures) w SQL na czysty, skalowalny i łatwy w utrzymaniu kod w technologiach Python / PySpark. Aktywny rozwój i utrzymanie dużej bazy kodu inżynierii danych (data engineering codebase), współdzielonej przez wiele zespołów. Projektowanie i rozwijanie modeli danych w ramach Medallion Architecture (warstwy Bronze / Silver / Gold). Implementacja kodu transformacyjnego klasy produkcyjnej (pakiety, moduły, reużywalne komponenty), wykraczającego poza użycie samych notebooków. Zastosowanie najlepszych praktyk inżynierii oprogramowania (Clean Code, OOP, modularyzacja, refaktoryzacja). Praca z bardzo dużymi wolumenami danych (petabajty) oraz wysoce równoległymi, opartymi na zdarzeniach (event-driven) transformacjami. Udział w code reviews oraz dyskusjach dotyczących projektowania technicznego architektury. Opcjonalnie: wsparcie workflowów orkiestracyjnych (np. Azure Data Factory) oraz rozwój procesów i CI/CD pipelines. Oczekujemy: Praktycznego doświadczenia technicznego (poziom Strong Mid-Level / Senior) – weryfikowanego na podstawie rzeczywistych umiejętności inżynieryjnych, a nie wyłącznie lat pracy. Bardzo dobrej, praktycznej znajomości języka Python oraz technologii PySpark. Udokumentowanego doświadczenia w pracy z Databricks oraz Delta Lake. Umiejętności pracy w dużych, współdzielonych środowiskach kodu. Biegłej znajomości SQL, szczególnie w zakresie czytania i rozumienia bardzo złożonej logiki. Solidnego doświadczenia w programowaniu obiektowym (OOP) oraz stosowaniu zasad Clean Code i refaktoryzacji. Praktyki w pracy z przepływami dla rozwiązań klasy enterprise (enterprise development workflows) oraz zdolności analitycznego rozkładania istniejącego kodu linijka po linijce. Silnych kompetencji w modelowaniu danych (transakcyjnym i analitycznym) oraz zrozumienia architektur wielowarstwowych (Bronze / Silver / Gold). Gotowości do przejścia rozmowy technicznej weryfikującej produkcyjny kod PySpark/Python. Mile widziane: doświadczenie z Azure Data Factory, Git, CI/CD pipelines, DevOps oraz narzędziami analitycznymi takimi jak Power BI Znajomości języka angielskiego na poziomie B2 lub C1 – umożliwiająca swobodną komunikację w międzynarodowym środowisku oraz mile widziana jest znajomość języka niemieckiego. Mile widziana jest dostępność ASAP; akceptowalny jest maksymalnie miesięczny okres wypowiedzenia, ze skutkiem na koniec miesiąca. Oferujemy: Długofalowa współpraca z wynagrodzeniem w przedziale 140-170 PLN netto/godz. + VAT. Wsparcie przy zakładaniu i prowadzeniu działalności gospodarczej, dla osób bez takiego doświadczenia. Sprawny proces rekrutacyjny - dwie rozmowy techniczne z managerami, online (każda maksymalnie po godzinie). Współpraca w pełni zdalna. Benefity - prywatna opieka medyczna, karta Multisport. Nowoczesny sprzęt zapewniany przez firmę, wraz z softem i konfiguracją.

🏢 Summary: Contract role for a Senior AWS DevOps Consultant to design and standardize a scalable cloud data platform with a strong focus on AWS Data Warehouse and platform engineering. The position centers on building reusable, multi-account AWS infrastructure and optimizing Redshift environments through automation and governance. The consultant will drive Infrastructure as Code, CI/CD, and architectural best practices to enable efficient data team scaling. 🗂️ Requirements: 5+ years of Cloud Infrastructure experience, Strong hands-on AWS expertise, Strong hands-on Terraform experience in multi-account environments, Experience with AWS Organizations, Experience designing platform-level solutions, Strong AWS Data Warehousing experience, Hands-on Redshift security and performance optimization, Experience with CI/CD pipelines, Experience with infrastructure automation, Understanding of cost optimization principles, Understanding of observability and scalability principles, Fluent English, Agile experience 📃 Skills: AWS, Terraform, Redshift, S3, Glue, GitHub, GitHubActions, JFrog, Python, Azure, CI/CD 🏢 Description: Senior AWS DevOps Consultant (Data Warehouse / Platform Engineering Focus) Location: Warsaw, Poland (Hybrid – minimum 2 days/week onsite) Rate: up to 220 PLN/hour About the Role We are looking for an experienced Senior AWS DevOps Consultant with a strong Data Warehouse background and a platform engineering mindset . The goal is not to hire general AWS engineers focused only on individual services or application-level work, but professionals who understand standardisation, scalable platform design, multi-account AWS environments, and reusable infrastructure capabilities . This role supports the development of a modern cloud data platform, enabling data teams to scale efficiently while maintaining strong architectural governance, automation, and performance standards. Key Responsibilities Data Warehouse Infrastructure (AWS / Redshift) Design, build, and optimize AWS-based Data Warehouse infrastructure Ensure scalable, secure, and well-documented Redshift environments Improve existing architecture and automate delivery processes Collaborate with cross-functional data engineering teams Platform Engineering & Infrastructure as Code (IaC) Develop and maintain infrastructure using Terraform in multi-account AWS environments Build reusable, standardized platform components rather than one-off solutions Implement CI/CD pipelines for infrastructure deployment Ensure robust, maintainable, and scalable cloud platform capabilities Mentorship & Knowledge Sharing Act as technical mentor for internal teams Promote platform engineering and AWS best practices Conduct pair programming and knowledge-sharing sessions Support teams in building strong AWS and data platform capabilities Requirements Must-have: 5+ years of experience in Cloud Infrastructure Strong hands-on expertise in AWS and Terraform (multi-account AWS Organizations) Experience designing platform-level solutions , not only service-level implementations Strong AWS Data Warehousing experience (especially Redshift: security, performance, optimization) Experience with CI/CD pipelines and infrastructure automation Strong understanding of cost optimization, observability, and scalability principles Ability to communicate complex technical topics clearly to stakeholders Fluent English and Agile experience Nice-to-have: AWS services: S3, Glue Tools: GitHub, GitHub Actions, JFrog, Python Experience with migration projects or multi-cloud environments (AWS + Azure) Knowledge of data governance and security practices Team 6 senior data warehouse engineers Strong background in Azure DWH, Redshift, and data engineering Agile/Scrum with Kanban practices

🏢 Summary: The offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.

🏢 Summary: Full-time B2B DataOps Engineer role on a long-term project within a large-scale analytical ecosystem for a telecommunications organization. The position focuses on building and automating end-to-end data processing and deployment workflows across on-premises and Kubernetes environments using GitOps principles. You will design, deploy, and optimize scalable data pipelines while integrating DevOps and Data Engineering practices. 🗂️ Requirements: 2.5+ years commercial experience in Data Engineering, DataOps or DevOps, Strong Python programming, Experience with PySpark and Pandas, Hands-on experience with Kubernetes and containerized applications, Experience with Helm, Experience with Git-based workflows, Experience building CI/CD pipelines, Understanding of GitOps principles, Experience supporting full application lifecycle, Linux command-line proficiency, Experience with LDAP, Active Directory, RBAC and TLS, Experience working with on-premises infrastructure, Polish language proficiency, Based in Poland with valid Polish passport 📃 Skills: Python, PySpark, Pandas, Kubernetes, Helm, Git, GitLab, Jenkins, ArgoCD, CICD, GitOps, Linux, LDAP, ActiveDirectory, RBAC, TLS 🏢 Description: DataOps Engineer (Poland) 💻 Hybrid (Remote with bi-weekly onsite meetings) 🕦 Full-time ☑️ B2B (long-term project) 🌍 Working hours: Central European Time (CET) We are looking for a DataOps Engineer to join a large-scale analytical ecosystem project for a leading telecommunications organization. This role is ideal for an engineer who enjoys solving complex data challenges, building automation from development through production deployment, and working across both Data Engineering and DevOps domains. You will be responsible for designing, developing, deploying, and optimizing large-scale data processing solutions while helping onboard new datasets and automate the entire delivery lifecycle using GitOps principles. The environment combines on-premises infrastructure, Kubernetes, and modern data technologies, requiring someone who is comfortable working beyond cloud-managed solutions. Must-Have’s 2.5+ years of commercial experience in Data Engineering, DataOps, DevOps, or related roles. Strong Python programming skills, including experience with analytical frameworks such as PySpark and Pandas. Experience working with Kubernetes and containerized applications. Hands-on experience with Helm. Experience with Git-based development workflows. Experience building and maintaining CI/CD pipelines using GitLab, Jenkins, ArgoCD, or similar tools. Understanding of GitOps principles and automated deployment processes. Experience supporting the full application lifecycle from development through production deployment. Linux proficiency, including command-line usage. Experience with authentication and authorization technologies such as LDAP, Active Directory, RBAC, and TLS certificate management. Strong analytical and problem-solving skills. Strong English communication skills. Polish language proficiency. Must be based in Poland and available to attend onsite meetings every two weeks. Must hold a valid Polish passport. Comfortable working with on-premises infrastructure environments. Nice to Have Experience with Apache Kafka. Experience with OpenSearch or Elasticsearch. Experience with OpenSearch Data Prepper, dbt, Kafka Streams, or similar ingestion technologies. Familiarity with Hadoop ecosystems. Experience with Ansible. Knowledge of SRE best practices, including SLOs and Error Budgets. Familiarity with Elastic Common Schema (ECS). Familiarity with TMForum standards. Degree from a leading technical university such as University of Warsaw, Warsaw University of Technology, AGH University of Science and Technology, or PJATK. Key Responsibilities Design, develop, and maintain data pipelines running on large-scale analytical platforms. Build automated processes for onboarding datasets and integrating new data streams. Develop and maintain GitOps-driven deployment workflows. Design and implement CI/CD pipelines for data and platform services. Deploy and manage applications running on Kubernetes-based environments. Monitor, troubleshoot, and optimize data processing workloads for performance and scalability. Collaborate with stakeholders to gather requirements and translate business needs into technical solutions. Support application lifecycle management, including design, implementation, deployment, and maintenance. Improve operational efficiency through automation and infrastructure standardization. Work closely with cross-functional teams to ensure reliable and scalable platform operations. Contribute to security, governance, and operational best practices across the environment. Get to know DevsData We are a technology consulting company and a recruitment agency, delivering software solutions to clients from Europe and the US. We work 100% remotely, in an international team, including people from Asia, London, or San Francisco. We employ people with experience in international corporations as well as students of the best technical and business universities. Find out more: https://devsdata.com/

🏢 Summary: Senior Big Data Engineer role focused on designing and optimizing large-scale data processing solutions using Spark and Scala within the financial sector. The position involves building resilient data pipelines, supporting production systems, and collaborating in Agile teams to deliver scalable data platforms. Hybrid work model based in Warsaw with up to two remote days per week. 🗂️ Requirements: 3-5 years experience in big data engineering, Strong expertise in Spark, Proficiency in Scala or Java, Knowledge of Python, Experience with DevOps practices, Experience with CI/CD tools, Understanding of microservices architecture, Fluent English, Legal right to work in the European Union 📃 Skills: Spark, Scala, Java, Python, DevOps, CI/CD, Microservices, Airflow, Git, Scrum, BigData 🏢 Description: Empower data-driven innovation — shape the future of financial technology! Warsaw-based opportunity with hybrid work model (up to 2 remote days per week). As a Senior Big Data Engineer (Spark/Scala) , you will be working for our client, a leader in structured finance within the global banking industry. You will contribute to building and optimizing a cutting-edge data platform that supports complex business processes and facilitates collaboration across multiple stakeholders in the finance sector. Join us to drive impactful data solutions that fuel digital transformation and open new avenues for growth. Your main responsibilities: Design and develop solutions for collecting, transforming, and processing large datasets efficiently. Analyze data from multiple sources and translate insights into technical specifications. Implement and industrialize reliable, scalable, and resilient data processing jobs using Spark and Scala. Conduct code reviews and collaborate with team members to ensure continuous improvement. Contribute to agile teams delivering value through Scrum cycles, supporting innovative project delivery. Stay up-to-date with evolving big data technologies and implement best practices. Support applications, troubleshoot production issues, and ensure high quality standards. Produce comprehensive technical documentation, test plans, and project artifacts. You're ideal for this role if you have: 3-5 years of professional experience in big data engineering, ideally within banking or finance. Strong expertise in Spark and Java or Scala, with additional knowledge of Python, DevOps, CI/CD tools, and microservices. Fluency in English (Polish and French are a plus). Analytical mindset with excellent problem-solving skills. Proactive attitude and strong teamwork skills across global teams. Effective communication skills and ability to work across different time zones. It is a strong plus if you have: Knowledge of Airflow, GIT, and modern data architecture strategies. Experience with Agile methodologies and delivering solutions in fast-paced environments. Language Required for the role: Fluent English (required) Eligibility for the role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.