Senior Data Engineer

Role overview Senior client-facing data engineering position focused on designing, building, and operating production-grade data platforms. Work spans ETL/ELT pipelines, dimensional warehouse models, and the ongoing cost and reliability optimization that keeps large data estates healthy, with patterns uncovered in the field fed back into an internal Platform Optimizer agent.

Responsibilities

- Build durable ETL/ELT pipelines and warehouse models using Airflow and dbt that hold up under production load - Optimize cost, performance, and reliability across Snowflake, BigQuery, Redshift, and Databricks environments - Own delivery end to end, from initial architecture through to handover, working directly with client teams - Translate real-world optimization findings into patterns the internal Platform Optimizer agent can reuse - Communicate tradeoffs, timelines, and risks clearly to non-technical client stakeholders

Requirements

- Five or more years building production data platforms, not just analytical notebooks - Strong SQL and Python, with deep expertise in at least one major cloud warehouse - Hands-on experience with Airflow and dbt in real deployments - Working knowledge of at least one of AWS, GCP, or Azure - Proven ability to lead client conversations and own problems independently - Fluent English and willingness to overlap with European working hours

Nice to have

- Prior contributions to internal tooling, agents, or reusable optimization libraries - Multi-warehouse or multi-cloud experience across the platforms listed above