In this role, you will:
- Build and maintain customer attribute and feature datasets in BigQuery, covering billing, usage, CDR, tenure, and sales/service events.
- Migrate the remaining pipelines away from a legacy data layer onto the new GCP platform.
- Develop and run Airflow (Cloud Composer) DAGs, Dataflow/Apache Beam pipelines, and Vertex AI pipelines, including their monitoring and alerting.
- Manage dataset access through AD groups, IAM, and dataset sharing, working with the platform team's Terraform.
- Work directly with data scientists and business stakeholders on requirements.
You will thrive if:
- You have at least 5 years of data engineering experience, including at least 2 years on GCP in production.
- You have strong SQL and BigQuery skills — partitioning, cost-aware query design, and large historical backfills.
- You're skilled in Python, with Airflow/Composer experience in production.
- You have experience producing datasets for ML — feature tables, point-in-time correctness, and train/test splits.
- You work with a Git-based workflow including code review and CI (GitHub Actions).
- Nice-to-have: You ideally hold a recent Finnish security clearance (turvallisuusselvitys), completed within the last one to two years — a recent clearance significantly speeds up Supo approval and shortens the time before production access is granted.
- As a plus: Dataflow/Apache Beam and Vertex AI pipeline experience and Terraform on GCP
- Finnish language skills are all a plus, since much of the source data and many stakeholders are Finnish-speaking.
This assignment supports a consumer data science organization's customer data and ML feature platform on GCP. It's expected to start as soon as possible, targeting mid-November 2026, running 5 months at 4 days/week, hybrid in Helsinki.