Senior Data Engineer
Job Summary
Role: Senior Data Engineer
Job Ref Id: JD-1292
Competence level: 5 years
Start date:
End date:
Extension option: Yes
Scope: 100%
Location: Stockholm
Remote work: On-site; remote considered
Language: English
Application deadline:
Number of consultants: 1
Security clearance: Not stated
About the assignment
We are looking for a Senior Data Engineer for an interim position in our Trust Intelligence & Calling department. Note: We prefer on-site but were considering remote candidate as well. We are re-architecting our data pipelines to meet stricter requirements on user-data lifecycle: encryption retention and deletion across historical and derived data. You lead the technical migration and establish the engineering processes that keep the pipelines reliable after it.Responsibilities
- Propose and drive the architecture for user-data handling across Airflow Spark dbt and BigQuery: encryption points derived tables backfills partitions.
- Migrate existing pipelines one at a time without changing their output behind a regression harness you build.
- Design the processes the team keeps after the migration: pipeline change review testing standards incident post-mortems release checklist.
- Remove duplicated steps and copy-pasted logic as you pass through each pipeline.
- Build verification jobs that prove the data-lifecycle rules hold end to end.
- Pair with and mentor a data engineer on the team with the goal that the team owns the migrated pipelines independently.
- Share pipeline maintenance and incident handling; fix root causes.
- Document decisions as short architecture decision records.
Requirements
Mandatory
Deep hands-on experience with Airflow Spark dbt BigQuery and Python.
At least one pipeline migration you led technically from start to finish.
Experience refactoring a live pipeline while proving its output is unchanged.
Experience introducing engineering processes (testing review incident handling) to a team and making them stick.
Mentoring experience with a concrete outcome.
Nice-to-have
A prior project on encryption at rest data retention or deletion compliance (for example GDPR).
Envelope encryption with a key manager (for example GCP KMS) BigQuery AEAD functions or Tink.
BigQuery column-level security policy tags Data Catalog.
Config Connector (KCC) for managing GCP resources from Kubernetes.
Events with Kafka.