Backend Engineer - Java

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 Summary: Data Engineer role focused on building and scaling data infrastructure for advanced robotics systems. The position involves designing reliable batch and real-time pipelines, optimizing ETL/ELT processes, and implementing data governance across cloud platforms. You will collaborate cross-functionally to deliver high-quality, scalable data solutions supporting company-wide analytics and operations. 🗂️ Requirements: BS/MS/PhD in Computer Science, Mathematics, Computer Engineering or related field, or equivalent practical experience, 1–5 years of professional experience, Proficiency in Python and SQL, Hands-on experience with Rust, Go, Java, C#, or C++, Experience with Kafka, Spark, and lakehouse formats (Icebert, DeltaLake), Experience with AWS, GCP, or Azure, Strong debugging and problem-solving skills, Willingness to work extended hours and weekends if needed, Ability to work full time onsite in San Francisco 📃 Skills: Python, SQL, Rust, Go, Java, C#, C++, Kafka, Spark, Icebert, DeltaLake, AWS, GCP, Azure, Clickhouse, Flink, Databricks 🏢 Description: About the Role Help us advance our robotics moonshot by scaling our data engineering efforts. Drive design and development of data infrastructure across our products and internal tools. You will play a critical role in working with a cross-functional team to architect and build advanced robotic systems. Responsibilities - Design, build, and maintain scalable, reliable data pipelines that support both batch and real-time analytics. - Develop and optimize ETL/ELT processes to ingest, transform, and integrate data from multiple sources into data warehouses and lakehouse platforms. - Drive and apply best practices in data modeling, pipeline architecture, query optimization, data quality, and data engineering standards. - Collaborate closely with finance, bizops, and engineering teams to understand data needs and deliver solutions. - Provide data engineering support to ensure data accessibility and usability company-wide. - Implement and maintain data governance frameworks to support compliance with internal policies and external regulatory requirements. - Evaluate and adopt modern data engineering technologies, tools, and best practices to improve scalability, reliability, and operational efficiency. - Document data engineering processes, designs, and architectures. Qualifications - BS/MS/PhD in Computer Science, Mathematics, Computer Engineering, or a related field, or equivalent practical experience. - 1-5 years of professional experience. - Proficiency in writing production-grade code in Python and SQL. - Hands-on experience with one of the following languages: Rust, Go, Java, C#, C++. - Strong debugging skills and the ability to diagnose and resolve issues efficiently. - Experience with Kafka, Spark and common lakehouse formats like Icebert, DeltaLake. - Experience working with cloud platforms like AWS, GCP, Azure. Preferred Experience - Experience with Clickhouse, Apache Flink, Databricks. - Experience on financial reporting and understanding of accountability. Additional Requirements - Willing to work extended hours and weekends if needed. - This position is based full time in our San Francisco headquarters. Compensation The pay range for this position at the start of employment is expected to be between $140,000 - $200,000/year. The exact offer may vary depending on job-related knowledge, skills, and experience. In addition to cash compensation, this position will also receive generous equity. Benefits - Unlimited Flexible Time Off. - Health insurance (medical, dental, vision). - Paid parental leave. - Commuter benefits including fully paid parking spots. - Referral bonus. - 401k retirement plan. - Equity program.

🏢 Summary: Senior Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!

🏢 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 Python Engineer role focused on building and scaling a cloud-native real-time Data Platform handling massive datasets. The position involves developing high-performance backend services, optimizing distributed systems, and integrating large-scale data storage solutions. Hybrid work model in Warsaw with employment benefits including private medical care and multisport card. 🗂️ Requirements: 8+ years of backend software development experience, Advanced Python expertise, Experience with scalable production-grade systems, Knowledge of concurrency and multiprocessing, Experience with Pandas or NumPy, Experience with Parquet or JSON data formats, Knowledge of relational and NoSQL databases, Experience with performance optimization and low-latency systems, Ability to use AI-assisted development tools responsibly 📃 Skills: Python, Pandas, NumPy, Parquet, JSON, SQL, NoSQL, API, OOP, Concurrency, Multiprocessing, Algorithms, Databases, Cloud 🏢 Description: For our client, a leading, high-growth global fintech company – we are looking for an experienced Senior Python Engineer to join a key engineering team responsible for the company’s core data foundation. The project focuses on building, optimizing, and scaling a cloud-native, high-throughput Data Platform designed to ingest, process, and distribute massive datasets in real-time. This platform serves as the backbone for various downstream analytical systems, requiring extreme reliability, performance, and scalability. This is a fantastic opportunity for a strong Python generalist who enjoys solving complex distributed system problems, optimizing data flows, and working with modern cloud architectures. Responsibilities Backend & Pipeline Development: Design and develop scalable backend services and high-performance data processing pipelines using Python. Performance Tuning: Identify bottlenecks and optimize system performance, focus on concurrency, throughput, and low-latency execution. Data Integration & Storage: Build robust integrations with modern cloud-native storage solutions and databases to manage large-scale datasets efficiently. Collaborative Engineering: Work closely with cross-functional technical teams to understand data requirements and deliver reliable API services and platform features. Engineering Excellence: Maintain top-tier coding standards, emphasizing clean code, robust testing (unit/integration), automation, and security. Requirements 8+ years of professional backend software development experience (with a strong track record in building scalable, production-grade systems). Deep expertise in Python (advanced OOP, concurrency/multiprocessing, memory management, data structures, and algorithms). Solid experience with data-centric libraries such as Pandas, NumPy, or similar data processing frameworks. Experience with large-scale data storage formats (e.g., Parquet, JSON, or column-oriented databases) and relational/NoSQL databases. AI-assisted development mindset: Comfortable utilizing AI tools  to accelerate delivery, while maintaining strong developer judgment regarding validation, testing, security, and refactoring. What our client offers: Hybrid work model in Warsaw (minimum 3 days a week in the office - strictly non-negotiable). Contract of Employment (UoP) with increased tax-deductible costs (KUP). Private medical care (including full dental care). Lunch card to cover your daily meals. Multisport card.

🏢 Summary: DevOps Engineer role focused on supporting and scaling modern data platforms by combining DevOps practices with data engineering expertise. The position involves building and maintaining CI/CD pipelines, managing cloud-based data infrastructure, and ensuring reliable, automated data workflows. You will collaborate with data teams to optimize performance, scalability, and security of data solutions. 🗂️ Requirements: 4–5 years experience in DevOps or similar role, Hands-on experience with Databricks, Strong experience with AWS, Experience building and maintaining CI/CD pipelines with Jenkins, Background in data engineering or data platforms, Basic to intermediate Python knowledge, Understanding of ETL/ELT processes, Knowledge of distributed data systems 📃 Skills: Jenkins, Databricks, AWS, Python, CICD, ETL, ELT, DevOps, DataEngineering, Cloud, DistributedSystems 🏢 Description: About the Role We are looking for a DevOps Engineer with a strong data background to support and scale modern data platforms. In this role, you will work at the intersection of DevOps and Data Engineering , ensuring reliable, automated, and efficient data pipelines and environments. You will be responsible for maintaining and improving CI/CD processes, supporting cloud-based data platforms, and collaborating with data engineers and analytics teams to enable smooth data operations. Key Responsibilities Design, implement, and maintain CI/CD pipelines using Jenkins . Manage and optimize data platforms based on Databricks . Build and maintain cloud infrastructure on Amazon Web Services . Support deployment, monitoring, and troubleshooting of data pipelines and workflows. Collaborate closely with data engineers to improve reliability and performance of data solutions. Automate infrastructure and operational processes. Ensure best practices in security, scalability, and performance across the platform. Required Skills & Experience 4–5 years of experience in a DevOps Engineer or similar role. Hands-on experience with Databricks . Strong experience with Amazon Web Services . Experience building and maintaining CI/CD pipelines using Jenkins . Background in data engineering or experience working with data platforms. Basic to intermediate knowledge of Python . Understanding of data pipelines, ETL/ELT processes, and distributed data systems. Strong problem-solving skills and ability to troubleshoot complex issues. Good communication skills and ability to work in cross-functional teams.

🏢 Summary: Senior backend engineering role focused on designing and operating large-scale batch and streaming data pipeline platforms with strong reliability and performance requirements. The position involves building distributed systems, pipeline orchestration services, and cloud-native platform capabilities using Java and modern data technologies. The role also includes technical leadership, CI/CD improvements, and collaboration across international engineering teams. 🗂️ Requirements: Strong backend engineering experience with Java, Experience building production-grade distributed systems, Expertise in software architecture and system design, Experience with high-throughput and low-latency systems, Knowledge of REST APIs and microservices, Hands-on experience with AWS and cloud-native design, Experience with Docker and Kubernetes, Experience with Flink, Spark, or Kafka, Familiarity with CI/CD pipelines and DevOps practices, Experience with Jenkins, GitLab, Git, and JIRA, Strong communication skills 📃 Skills: Java, Flink, Spark, Kafka, AWS, EMR, S3, REST, Microservices, Docker, Kubernetes, Jenkins, GitLab, Git, JIRA, HTTP 🏢 Description: The Pipeline Management team builds and operates a core platform that powers large-scale batch and streaming data pipelines across HERE’s Data Platform. Our platform enables internal teams and customers to design, deploy, and operate data pipelines at scale, supporting mission-critical workloads with strong reliability and performance requirements. Lead the design and development of pipeline management services and APIs Own and evolve key platform components, including pipeline orchestration, scheduling, and workflow state management Drive architecture for high-throughput, low-latency distributed systems Partner with Product and engineering teams to deliver scalable data platform capabilities Mentor engineers and provide technical leadership across a distributed team Improve system reliability, observability, and SLA adherence for production services Contribute to CI/CD, automation, and engineering best practices across the platform Technology Stack: You will work with a modern data platform ecosystem including: Data Processing: Apache Flink, Apache Spark Backend & Services: Java (primary), REST APIs, microservices Streaming & Messaging: Apache Kafka Cloud & Infrastructure: AWS (EMR, S3) Platform Services: Pipeline Service, Scheduler, State Service, Coordinator CI/CD & Tooling: Jenkins, GitLab pipelines, Git, JIRA Who are you? Strong backend engineering experience with Java (preferred), building production-grade distributed systems Expertise in software architecture and system design Experience building and operating high-throughput, low-latency, highly reliable distributed systems Solid understanding of REST APIs, HTTP, and microservices architectures Hands-on experience with cloud platforms (AWS preferred) and cloud-native design Experience with containerization and orchestration (Docker, Kubernetes) Experience with data processing and streaming systems (e.g., Flink, Spark, Kafka) Strong familiarity with CI/CD pipelines and engineering tools (e.g., Jenkins, GitLab, Git, JIRA) Experience applying DevOps practices to improve system reliability and delivery velocity Strong communication skills with the ability to clearly explain complex concepts Nice to Have Experience with pipeline orchestration platforms or workflow engines Exposure to large-scale data platforms or multi-tenant systems Experience with cloud platform migrations or modernization initiatives What we offer: Work on on globally deployed automotive navigation and mapping products Collaboration with an experienced, international engineering organization Truly international team of fantastic & talented people from 60+ countries worldwide, working from strong tech hubs located in Europe, the US, and Asia, along with multiple smaller locations Flexible working hours & a flexible approach to office vs. remote work Medical coverage for you and your family Yearly variable bonus This role is eligible for the Creative Tax Incentive scheme in Poland (KUP) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case)

🏢 Summary: Senior Backend Developer (remote, 12-month contract) focused on building scalable data processing systems and robust data pipelines. The role involves designing system architecture, coding for scale, and collaborating across teams while experimenting with new technologies and MVPs. 🗂️ Requirements: BSc in Software Engineering, Computer Science or related field, 5+ years of experience with Python, Hands-on experience with data pipelines, Experience designing scalable system architectures, Experience in backend software development 📃 Skills: Python, AWS, CI/CD, DevOps, SQL, ElasticSearch, OpenSearch, Neptune, Neo4j 🏢 Description: Start: ASAP Work model: Remote Length of contract: 12 months + extensions We’re looking for a Senior Backend Developer with a data pipeline emphasis with a strong understanding of and hands-on experience with broad software development, i.e., system architecture, coding for scale, and communicating possibilities for what can be built and maintained, as well as a love for experimenting and building MVPs. Core Responsibilities: Design and implement software architectures for scalable data processing systems. Develop and maintain data pipelines for efficient data ingestion and processing. Collaborate with cross-functional teams to define and streamline software development processes. Participate in code reviews and maintain high software quality standards. Experiment with new technologies and frameworks to enhance system performance. Key Requirements: BSc in Software Engineering, Computer Science, or other relevant field 5+ years of experience with Python Experience with data pipelines Nice to Have: Experience with one or more AWS services AWS DevOps CI/CD Pipelines Relational databases ElasticSearch/OpenSearch Graph databases (e.g., Neptune or Neo4j)