Data Engineer (Python & AWS)

🏢 Summary: The offer is for an experienced Python Data Engineer to build scalable, cloud-based data and analytics solutions for global financial institutions. The role focuses on designing distributed data pipelines, enhancing system reliability, and developing financial and AI-driven data platforms. You will work with modern cloud and AI tools to advance enterprise data architecture and analytics capabilities. 🗂️ Requirements: 4+ years of professional experience in Python data or software engineering, Strong knowledge of data architecture, data modeling, and data warehousing, Advanced SQL skills and complex query writing, Experience building scalable distributed data pipelines, Hands-on experience with cloud environments (AWS preferred), Understanding of event-driven architectures, Experience with debugging and system reliability practices 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Opportunity for an experienced Python Data Engineer to build scalable data platforms and analytics systems for global financial institutions. The role focuses on designing cloud-based data pipelines, enhancing system reliability, and integrating modern AI tools into engineering workflows. You will collaborate across distributed teams to deliver high-quality solutions in enterprise data, risk analytics, and AI-driven metadata applications. 🗂️ Requirements: 4+ years of professional experience in software or data engineering using Python, Strong knowledge of data architecture, data modeling, and data warehousing, Ability to write complex SQL queries and perform advanced debugging, Experience building scalable, distributed data pipelines in cloud environments, Experience with AWS, Familiarity with event-driven architectures 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For: Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Lead Data Engineer role focused on driving AI initiatives and building scalable cloud-based data architectures in a global environment. The position involves technical ownership of data platforms, designing secure and high-performing systems, and leading data engineering efforts in a DevOps setting. The role emphasizes AI integration, cloud infrastructure, and enterprise-grade data governance. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python in production, Strong experience designing and scaling complex data systems, Hands-on experience with AI technologies, Hands-on experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs and data integration, Experience with automation tools, Knowledge of data governance practices, Understanding of data security and compliance standards, Proven experience leading and mentoring engineers 📃 Skills: Python, SQL, AWS, Azure, Java, AI, RAG, MCP, APIs, DevOps, Automation, Monitoring, Cloud, DataEngineering, DataPipelines, Governance, Security, Compliance, Backend 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Senior Backend Engineer role focused on modernising and expanding a secure AWS serverless platform in the healthcare sector. The position involves building event-driven backend services, migrating Azure components to AWS, and integrating Salesforce within a compliant cloud environment. This is a hands-on remote contract role delivering production-grade solutions under tight timelines. 🗂️ Requirements: 4+ years backend engineering experience, 2+ years AWS serverless production experience, Strong commercial experience with Python or TypeScript, Hands-on experience with AWS Lambda, API Gateway, EventBridge, SQS, SNS, Step Functions, Experience with RDS, DynamoDB, S3, Secrets Manager, Terraform for application-level infrastructure, Salesforce API integration experience (REST or Platform Events), Strong knowledge of REST APIs and event-driven architectures, GitLab with CI/CD workflows, Familiarity with SOC 2 or HIPAA compliance 📃 Skills: Python, TypeScript, AWS, Lambda, APIGateway, EventBridge, SQS, SNS, StepFunctions, RDS, DynamoDB, S3, SecretsManager, Terraform, GitLab, CI/CD, Salesforce, REST, Azure, AzureFunctions, AzurePipelines 🏢 Description: Senior Backend Engineer (AWS Serverless) About the Role We’re looking for experienced Senior Backend Engineers to join a cloud modernisation project in the healthcare sector. The team is responsible for rebuilding and expanding a secure AWS-based platform, migrating selected Azure services, and delivering scalable integrations with Salesforce and other external systems. This is a hands-on engineering role focused on backend services, serverless infrastructure, and event-driven architectures. You’ll work closely with cloud engineers, platform teams, and stakeholders to deliver production-ready solutions under tight delivery timelines. The project includes both modernisation of existing systems and development of new integrations — this is not a greenfield environment. Contract Type: B2B Work Mode: 100% Remote Time Zone: CET/CEST (Poland) — occasional meetings after 18:00 Project Overview The client is operating in the medical industry and is currently modernising their cloud ecosystem to support secure and compliant data processing workflows. The engineering team will focus on: Building AWS serverless services and APIs Designing event-driven integrations with Salesforce Migrating Azure-based components to AWS Rebuilding repositories and CI/CD processes in GitLab Delivering secure architectures aligned with SOC 2 and HIPAA standards Technology Stack Backend & Cloud Python TypeScript AWS Lambda API Gateway Step Functions EventBridge SQS / SNS Data & Infrastructure RDS DynamoDB S3 AWS Secrets Manager Terraform GitLab CI/CD Integrations & Compliance Salesforce REST API Salesforce Platform Events SOC 2 HIPAA Confluence Jira Responsibilities Backend Engineering & Integrations Build and maintain scalable serverless services on AWS Design and implement Salesforce-to-EventBridge integration patterns Develop secure architectures for client file transfer and data synchronisation Create reusable integration standards for event-driven and bulk-processing workflows Design and maintain RESTful APIs and asynchronous processing pipelines Migration & Platform Modernisation Rebuild selected Azure Functions and Azure Pipelines within AWS environments Support repository migration and CI/CD transition to GitLab Contribute to infrastructure and deployment automation using Terraform Engineering Quality & Delivery Participate in code reviews and maintain production-grade engineering standards Create and maintain technical documentation in Confluence Work within agile delivery processes including daily standups, sprint reviews, and retrospectives Collaborate closely with cloud engineers and platform stakeholders What We’re Looking For Required Skills & Experience 4+ years of backend engineering experience 2+ years working with AWS serverless technologies in production Strong commercial experience with Python and/or TypeScript Hands-on experience with: AWS Lambda API Gateway EventBridge SQS / SNS Step Functions Experience with RDS, DynamoDB, S3, and Secrets Manager Terraform experience focused on application-level infrastructure Experience integrating Salesforce APIs (REST and/or Platform Events) Strong understanding of REST APIs and event-driven architectures GitLab experience including CI/CD integration workflows Familiarity with SOC 2 and/or HIPAA compliance requirements Experience creating production-level technical documentation Nice to Have Azure Functions or Azure Pipelines migration experience Healthcare or medical-sector project background Experience with ETL / ELT or bulk data processing pipelines API test automation experience

🏢 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: 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: Remote DevOps Engineer role focused on building and maintaining a self-service SDLC platform in AWS, with strong emphasis on automation, CI/CD, and Infrastructure as Code. The position involves designing cloud architecture, improving developer experience, and ensuring reliability and security of environments. The role offers real impact on DevOps standards within a modern, cloud-native ecosystem. 🗂️ Requirements: Commercial experience as DevOps Engineer or Cloud Engineer, Strong AWS experience, Proficiency in Python for automation, Proficiency in Bash for automation, Hands-on experience with Infrastructure as Code, Experience designing and maintaining CI/CD pipelines, Knowledge of Docker, Knowledge of Kubernetes, Ability to work in English at B2/C1 level 📃 Skills: AWS, Python, Bash, Terraform, CloudFormation, CDK, SAM, Jenkins, Bamboo, Docker, Kubernetes, CI/CD, IaC 🏢 Description: Nasz Klient to międzynarodowa organizacja technologiczna rozwijająca nowoczesne rozwiązania chmurowe wspierające zespoły produktowe i inżynierskie na całym świecie. Projekt koncentruje się na budowie oraz rozwoju platformy samoobsługowej wspierającej pełny cykl życia aplikacji, ze szczególnym naciskiem na automatyzację, niezawodność oraz usprawnianie pracy zespołów deweloperskich. Szukamy doświadczonej osoby na stanowisko DevOps Engineer, która chce mieć realny wpływ na rozwój środowiska chmurowego, standardy inżynierskie oraz narzędzia wykorzystywane przez zespoły technologiczne. 📍 TRYB PRACY: 100% zdalnie 🧑‍💻 CZYM BĘDZIESZ SIĘ ZAJMOWAĆ? Projektowaniem, rozwijaniem i utrzymywaniem platformy samoobsługowej wspierającej pełny cykl życia aplikacji Tworzeniem oraz rozwijaniem procesów CI/CD z wykorzystaniem Bamboo , Jenkins lub podobnych narzędzi Implementacją rozwiązań IaC z wykorzystaniem CloudFormation , CDK , Terraform oraz SAM Integracją i rozwojem usług opartych o AWS , w tym rozwiązań serverless oraz PaaS Monitorowaniem wydajności, dostępności i bezpieczeństwa środowisk oraz wspieraniem działań związanych z obsługą incydentów Usprawnianiem automatyzacji, procesów oraz narzędzi wykorzystywanych przez zespoły deweloperskie 🔍 CZEGO OD CIEBIE OCZEKUJEMY? Must have: Komercyjne doświadczenie na stanowisku DevOps Engineer lub Cloud Engineer ze szczególnym uwzględnieniem środowiska AWS Bardzo dobra znajomość Python oraz Bash w kontekście automatyzacji procesów Praktyczne doświadczenie z usługami AWS oraz rozwiązaniami IaC Doświadczenie w projektowaniu, wdrażaniu i utrzymaniu procesów CI/CD Znajomość technologii Docker oraz Kubernetes Znajomość języka angielskiego na poziomie minimum B2/C1 umożliwiająca swobodną komunikację w międzynarodowym środowisku Nice to have: Certyfikaty AWS Solutions Architect oraz/lub AWS DevOps Engineer Professional Doświadczenie w pracy przy dużych, międzynarodowych platformach technologicznych Znajomość środowiska Microsoft Azure 🤝 DLACZEGO WARTO? 💰 Konkurencyjne warunki współpracy dopasowane do poziomu doświadczenia i kompetencji 🚀 Realny wpływ na architekturę platformy, standardy DevOps oraz rozwój środowiska chmurowego 🌍 Współpraca z doświadczonym zespołem działającym w międzynarodowym środowisku 🏠 Możliwość pracy w 100% zdalnej oraz elastyczne godziny współpracy 🛠️ Praca z nowoczesnym stackiem technologicznym skoncentrowanym na automatyzacji, jakości i rozwiązaniach chmurowych Dziękujemy za wszystkie zgłoszenia! Skontaktujemy się z wybranymi osobami. TQLO Sp. z o.o. – Agencja Zatrudnienia (nr KRAZ 33580)

🏢 Summary: Remote DevOps Engineer role focused on building and optimizing AWS-based infrastructure, managing EKS clusters, and developing CI/CD pipelines using Harness. The position involves Infrastructure as Code implementation, automation with Python and Shell scripting, and support for containerized and database-driven environments. Working hours are aligned to 12:30PM–9:00PM CEST. 🗂️ Requirements: 5+ years of DevOps experience, Strong AWS experience, Hands-on experience with EKS, Experience with Harness CI/CD pipelines, Proficiency in Python, Proficiency in Unix/Shell scripting, Experience with Terraform or CloudFormation, Knowledge of Oracle or SQL Server, Experience with Docker, Bachelor’s degree in Computer Science or related field 📃 Skills: AWS, EKS, Kubernetes, Harness, Terraform, CloudFormation, Python, Shell, Docker, EC2, VPC, IAM, S3, EFS, CloudWatch, SecretsManager, Oracle, SQLServer, CI/CD 🏢 Description: 💡 We are looking for a DevOps Engineer with strong hands-on experience in AWS cloud , EKS, automation, CI/CD pipelines , and Infrastructure as Code. ◽️ Remote from Poland ✔️ Expected working hours will be from 12:30PM to 9:00PM CEST Key Responsibilities: - Build, maintain, and optimize CI/CD pipelines using Harness. - Manage and operate EKS clusters and Kubernetes workloads. - Implement Infrastructure as Code (IaC) using Terraform or CloudFormation. - Automate deployment and environment tasks using Python and Unix/Shell scripting. - Manage AWS services such as EC2, VPC, IAM, S3, EFS, CloudWatch, Secrets Manager, etc. - Support containerization using Docker. - Work with Oracle/SQL Server databases. - Troubleshoot infrastructure, deployment, pipeline, and cluster issues. Must‑Have Skills: - 5+ years of DevOps experience. - Strong experience with AWS and EKS. - Hands-on experience with Harness pipelines. - Proficiency in Python, Unix/Shell scripting, and IaC (Terraform/CloudFormation). - Good knowledge of relational databases (Oracle/SQL Server). - Strong problem-solving and communication skills. Prefer to have/familiar with: - Experience with AWS components such as ECR, ALB/NLB, Lambda, API Gateway, SQS/SNS. - Experience working with job schedulers like Autosys. - Experience working in Investment banking domain Qualifications: Bachelor’s degree in Computer Science or a related field. The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email, or face to face. 📩 If you’re interested and meet the qualifications, please send your CV to Alina Pchelnikova at alina.pchelnikova@dcvtechnologies.co.uk