Senior Data Platform Engineer, WARSZAWA

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.

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.

,[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., 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., 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., 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: Python, Java, MySQL, AWS DynamoDB, Redis, Data pipelines, Kafka, Spark, ETL, Communication skills, Cloud, NoSQL, PostgreSQL