Senior Data Engineer (GenAI / LLM)

As a recruitment company, Aperture Cloud understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for: Senior Data Engineer (GenAI / LLM) Responsibilities: Design and implement LLM‑ and agent‑assisted workflows to improve developer productivity and reliability of data pipeline delivery Build and enhance AI‑driven automation for engineering processes, including: pull request automation, quality gates and assistive development tooling Implement AI‑supported schema review and governance gates within the canonical message lifecycle Drive AI‑powered test automation, including automated E2E test generation and quality validation Develop and maintain data packaging pipelines transforming source data into canonical message formats aligned with Data Packaging Framework and Availability Layer patterns Build and manage SQL‑based data transformations and configuration‑driven pipelines Support the canonical message lifecycle, including:schema validation, versioning, compatibility checks and publishing workflows Contribute to framework releases, operational stability, and documentation Maintain and update Architecture Decision Records (ADRs) Requirements: 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) 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: 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 Offer: Private medical care Co-financing for the sports card Constant support of dedicated consultant Employee referral program