The posting
Role: Senior Data Engineer Job Ref Id: JD-1292 Competence level: 5+ years Start date: 2026-11-09 End date: 2027-04-30 Extension option: Yes Scope: 100% Location: Stockholm Remote work: On-site; remote considered Language: English Application deadline: 2026-11-01 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 we're 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.



