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Senior Data Engineer / Data Pipeline Architect
Datamatics Technologies
Source: Headcount Labs · original listing ↗
Job data: Headcount Labs, ODbL 1.0. Job descriptions belong to their employers.
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About this role
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 • Minimum 5 years of relevant professional experience (5–10 years overall). • Deep hands-on experience with Airflow, Spark, dbt, BigQuery, and Python. • Proven experience technically leading at least one complete data pipeline migration from start to finish. • Experience refactoring production data pipelines while verifying that their outputs remain unchanged. • Experience establishing and implementing engineering processes for testing, code reviews, and incident management. • 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 .