Senior Data Engineer

– Proven experience as a Senior Data Engineer delivering production-grade data pipelines
– Strong SQL skills: complex transformations, relational modelling, query-plan analysis and optimisation
– Hands-on experience with graph databases and knowledge graphs, including ontology and entity/relationship modelling
– Practical experience designing NoSQL data models (partitioning, indexing, consistency trade-offs)
– Strong Python skills (or equivalent) for orchestration, transformation and testing
– Experience building reusable pipeline frameworks across multiple sources or domains
– Good understanding of batch and event-driven processing, incremental loads, idempotency and backfill strategies
– Experience with structured and unstructured data, including document content and metadata
– Solid knowledge of data quality, schema evolution, lineage and data lifecycle management
– Experience with cloud data services, orchestration tools, CI/CD and monitoring
– Clear communication and experience working across engineering, architecture and business teams

• Prestigious position at one of the world’s largest banks
• Stable, long-term projects
• Competitive salary with a B2B contract
• Hybrid work (6 days per month from the office in Cracow)
• Private healthcare and multisport card
• Personal growth and development opportunities with the possibility to rotate between projects

,[Design, build and run end-to-end pipelines covering ingestion, extraction, transformation, enrichment, validation and publication, Develop reusable connectors and processing components for structured and unstructured sources (APIs and other interfaces), Build reliable pipelines with idempotent writes, deduplication, retries, replay, backfills and recovery from partial failures, Design incremental and full-load patterns suited to each source’s volume and change behaviour, Develop SQL data models and transformations, with a focus on integrity and query performance, Design graph schemas and translate ontology concepts into implementable models, mapping source data to the knowledge graph, Build graph loading and query patterns that preserve identifiers, relationships, provenance and lineage, Design NoSQL models around access patterns, and integrate relational, graph and NoSQL stores, Implement data quality controls, lineage tracking and operational monitoring (throughput, freshness, failure rates), Help set standards for security, access control, observability and data lifecycle across pipelines, Contribute to automated testing, schema migrations, CI/CD and production support, Work with analysts, architects, engineers and business stakeholders to turn source requirements into technical designs] Requirements: Python, SQL, NoSQL, CI/CD Additionally: Sport subscription, Training budget, Private healthcare, Free coffee, Gym, Bike parking, Playroom, Free snacks, Mobile phone, Free parking.