Data Governance Engineer

Kraken is a mission-focused company rooted in crypto values, seeking a Data Governance Engineer to join their Data Platform Team. The role involves ensuring data is discoverable, well-documented, auditable, and reliable, supporting foundational capabilities for data usage at scale.

Responsibilities:

• Support metadata and catalog initiatives, including column-level tagging, dataset documentation, and ownership attribution
• Contribute to data lineage and governance practices, helping improve audit readiness and visibility across pipelines and products
• Support and maintain Airflow DAGs, including simple pipeline changes, operational fixes, and automation tasks
• Assist with CI/CD workflows related to data pipelines, deployments, and platform tooling
• Help improve data pipeline reliability and consistency, partnering with senior engineers on enhancements and fixes
• Contribute to automation of reports and dashboards, enabling self-serve analytics for internal teams
• Support adoption of data governance standards across teams, including documentation, processes, and tooling
• Assist internal stakeholders with ad-hoc data questions, process improvements, and platform-related enhancements

Requirements:

• 2+ years of experience in data governance, data engineering, analytics engineering, or a closely related technical role
• Hands-on exposure to data governance concepts, including: Metadata management, Data lineage (dataset- and column-level), Data catalogs (e.g. DataHub or similar tooling), Audit and compliance requirements
• Experience supporting or contributing to governance initiatives, such as documentation standards, ownership models, or data quality practices
• Hands-on experience with data governance tools like Datahub or similar at a major multi-source high volume data system
• Strong Python fundamentals, used for automation, metadata ingestion, or governance-related tooling
• Solid SQL skills for data discovery, validation, and audit support
• Basic understanding of how data pipelines work end to end, sufficient to reason about lineage, dependencies, and data quality
• Familiarity with Airflow or workflow orchestration in a support or operational capacity
• A curious, problem-solving mindset and willingness to grow in a fast-moving data platform environment
• Dashboards or BI tools (e.g. Looker, QuickSight, Tableau)