Data Platform Engineering Team Lead JB-4409

An innovative start-up that developed a cybersecurity product for the automotive industry is searching for a Data Platform Engineering Team Lead.

Responsibilities:

Spend about 70% of your time coding, building and tuning the data lake (Iceberg + Trino + dbt) for fast, cost-effective queries.

Lead and mentor skilled data engineers: code reviews, pairing, growth plans, and future hiring.

Own the platform roadmap including schema design, query-engine upgrades, governance and new technology choices.

Design and maintain well-partitioned tables and views so DS, DA, users and product teams can work faster and effectively.

Automate ETL data-digests and ML model training with Prefect, and own the pipelines for deployments (GitHub Actions → Kubernetes), data-quality checks, monitoring and SLOs.

Enhance and scale our ML platform, and automate the machine-learning lifecycle (MLflow, feature stores, model builds and deployment).

Stay focused on the data lake.

8+ years of software/data engineering (strong Python preferred; JVM/Go welcome).

4+ years working with large-scale data lakes/lakehouses, including Iceberg (or similar formats). Experience with Apache Spark for heavy batch / ML pipelines is a plus.

2+ years leading engineers, while still being hands-on.

Solid SQL skills and experience with much of our stack: Trino/Presto, dbt, Iceberg, Prefect/Airflow, Kubernetes, GitHub Actions.

A builder’s mindset: measure, improve, document, then automate.

Clear communication in English and a collaborative attitude.