Senior Data Engineer / Data Pipeline Architect

Location: Stockholm, Sweden (Hybrid – Travel Required)
Experience Required: 5 to 10 years
Duration: 6 months (Extendable)
Employment Type: FTE
Working Mode: Hybrid (Travel Required)
Language: English
Start: November 9, 2026 – April 30, 2027

We are looking for an experienced Senior Data Engineer / Data Pipeline Architect for an assignment in Stockholm focusing on data pipeline modernization, data security, and technical architecture.

The assignment involves leading the technical migration of existing data pipelines to meet stricter requirements for encryption, data retention, and deletion of user data, including historical and derived datasets.

Key Responsibilities

• Design and drive the architecture, migrating pipelines incrementally while ensuring existing outputs remain unchanged.
• Establish sustainable engineering processes for testing, code reviews, incident management, and releases.
• Combine architectural leadership with hands-on engineering using Airflow, Spark, dbt, BigQuery, and Python.
• Collaborate closely with and mentor a Data Engineer within the team, ensuring long-term ownership, reliability, and independent maintenance of the migrated pipelines.

Must-Have Requirements

1. Minimum 5 years of relevant professional experience (5–10 years overall).
2. Deep hands-on experience with Airflow, Spark, dbt, BigQuery, and Python.
3. Proven experience technically leading at least one complete data pipeline migration from start to finish.
4. Experience refactoring production data pipelines while verifying that their outputs remain unchanged.
5. Experience establishing and implementing engineering processes for testing, code reviews, and incident management.
6. Demonstrated mentoring experience with measurable outcomes.

Education

• Minimum Bachelor's degree (or equivalent).

Nice-to-Have

• Experience with encryption at rest, data retention, or data deletion compliance (e.g., GDPR).
• Experience with envelope encryption and key management solutions (e.g., GCP KMS, AEAD functions, or Tink).
• Knowledge of BigQuery column-level security, policy tags, and Data Catalog.
• Experience with Config Connector (KCC) for managing GCP resources through Kubernetes.
• Experience with event-driven architectures using Kafka.