Senior Data Engineer / Data Pipeline Architect

We are seeking a seasoned Senior Data Engineer / Data Pipeline Architect for a hybrid role based in Stockholm, Sweden. This position focuses on modernizing data pipelines, enhancing data security, and refining technical architecture. The successful candidate will lead the technical migration of existing data pipelines to comply with stricter requirements around encryption, data retention, and user data deletion, including historical and derived datasets. The role requires a blend of architectural leadership and hands-on engineering, with collaboration and mentorship responsibilities within the team. This is a full-time engagement initially for six months, with the possibility of extension, starting November 9, 2026.

Key Responsibilities

- Design and lead the incremental migration of data pipelines, ensuring that existing outputs remain consistent throughout the process.
- Establish and maintain sustainable engineering processes covering testing, code reviews, incident management, and release workflows.
- Apply hands-on expertise with technologies such as Airflow, Spark, dbt, BigQuery, and Python to support architectural goals.
- Collaborate closely with and mentor a Data Engineer, fostering long-term ownership, reliability, and independent maintenance of the migrated pipelines.

Required Qualifications

- A minimum of 5 years of relevant professional experience, with an overall experience range of 5 to 10 years.
- Deep hands-on experience with Airflow, Spark, dbt, BigQuery, and Python.
- Proven track record of technically leading at least one complete data pipeline migration from inception to completion.
- Experience refactoring production data pipelines while ensuring that outputs remain unchanged and reliable.
- Demonstrated ability to establish and implement engineering processes such as testing, code reviews, and incident management.
- Strong mentoring skills with measurable outcomes in team development.
- Bachelor’s degree or equivalent educational qualification.

Preferred Qualifications and Benefits

- Experience with encryption at rest, data retention policies, or compliance with data deletion regulations such as GDPR.
- Familiarity with envelope encryption and key management solutions, for example, GCP KMS, AEAD functions, or Tink.
- Knowledge of BigQuery’s column-level security, policy tags, and Data Catalog features.
- Experience using Config Connector (KCC) to manage Google Cloud Platform resources through Kubernetes.
- Exposure to event-driven architectures, particularly using Kafka.

This role requires fluency in English and involves hybrid working arrangements with travel as needed. The assignment is initially set for six months, with potential for extension, offering an exciting opportunity to lead critical data infrastructure modernization within a dynamic environment.