Senior Data Engineer

💻 Ework Group - founded in 2000, listed on Nasdaq Stockholm, with around 13,000 independent professionals on assignment - we are the total talent solutions provider who partners with clients, in both the private and public sector, and professionals to create sustainable talent supply chains. With a focus on IT/OT, R&D, Engineering and Business Development, we deliver sustainable value through a holistic and independent approach to total talent management. By providing comprehensive talent solutions, combined with vast industry experience and excellence in execution, we form successful collaborations. We bridge clients and partners & professionals throughout the talent supply chain, for the benefit of individuals, organizations and society. 🔹 For our Client from banking industry we are looking for🔹 Senior Data Engineer 🔹 We are looking for a GenAI/LLM-oriented engineer to join the team building and operating the Data Packaging Framework within the Availability Layer, transforming source data into canonical messages for end-to-end delivery and provisioning of Data Products across domains. A key part of the role is to embed AI into the engineering lifecycle - enhancing automation and quality gates around schema evolution, validation, publishing and end-to-end testing, including AI-driven review steps already present in the canonical-message pipeline approach. Key Responsibilities GenAI/LLM-enabled engineering automation: Build and evolve LLM/agent-assisted workflows that improve developer productivity and reliability in data pipeline delivery (e.g., PR automation, quality gates, assistive tooling). Implement and enhance AI-supported schema review and governance gates as part of canonical message lifecycle automation Drive AI-supported test automation, including automated E2E test generation and quality validation approaches Core data engineering: Develop and maintain data packaging pipelines transforming source-specific data into canonical message formats aligned with DRA 3 / Availability Layer patterns. Build and manage SQL-based transformation logic and configuration-driven pipelines. Support the canonical message schema lifecycle: validation, versioning, compatibility checks, and publishing workflows. Contribute to framework releases, operational stability, documentation, and Architecture Decision Records (ADRs). Must-have knowledge and experience Strong AI / GenAI capability: Hands-on experience building LLM-powered automation for engineering workflows (e.g., review gates, quality checks, assistant tooling for dev/test/docs). Experience with AI-assisted review/approval flows and integrating AI steps into CI/CD-style pipelines Experience with AI-assisted test generation / test automation concepts Strong engineering discipline around quality and safety for AI outputs (evaluation mindset, reproducibility, traceability) Core data engineering: Strong experience in data engineering and distributed processing; practical delivery mindset. Hands-on experience with Kafka and SQL-based transformations. Experience with batch/stream processing frameworks (e.g., Flink or Spark) Familiarity with schema formats and lifecycle (e.g., JSON/Avro/XSD) and versioning/compatibility concepts. Experience working with Git workflows and Kubernetes environments. CI/CD and build pipeline experience (Bazel + Tekton) Nice-to-have knowledge and experience Experience with Data Reference Architecture / data product model Knowledge of Airflow, Snowflake, Iceberg, or similar data platforms Exposure to data governance, metadata, and lineage concepts Experience in banking or other regulated environments Possible locations: Gdynia, Gdansk & Warsaw. Hybrid setup for this role is 3 days per week from the office. Contact person: dominika.kisiel@eworkgroup.com Client code: BN01 Do you know someone who would fit this position? Recommend a candidate by sending her/his CV to: polecenia@eworkgroup.com Whistleblowing Policy, which provides guidelines for reporting misconduct can be found on Ework website: https://www.eworkgroup.com/about-us/our-responsibility