Data Governance Engineer
Builds automation, tools, and frameworks for data governance, quality, and compliance using Python and Terraform. Partners with engineering teams to implement trust signals, scorecards, and AI-enhanced workflows for reliable data at scale. Requires 5+ years experience.
About the job
Responsibilities
- Build Data Trust Infrastructure: Design and implement trust scorecards, trust signals, and quality indicators that give data consumers real-time visibility into data reliability - and partner with producers upstream to embed quality checks at the source before issues propagate downstream.
- Drive Data Quality Strategy: Own and evolve Chime's data quality strategy end-to-end. Design and partner with engineering teams to implement data quality frameworks and monitoring systems that proactively identify, surface, and resolve data issues at scale.
- Develop and Implement Data Governance Policies: Create and enforce policies for data classification, quality, and lifecycle management, ensuring data integrity and compliance with SOX and other applicable regulatory standards.
- Enable the Data Catalog: Collaborate on the development, adoption, and enrichment of Chime's data catalog - improving discoverability, context richness (lineage, ownership, definitions, usage guidance), and the overall experience of working with Chime's data.
- Automate Governance Processes: Develop and deploy automation solutions for data governance tasks, such as metadata management, data lineage tracking, access controls, and quality remediation workflows.
- Champion SOX Compliance: Play an active role in Chime's SOX compliance efforts, ensuring that data governance practices, controls, and audit trails meet regulatory requirements and are well-documented.
- Lead AI Adoption for Data Governance: Serve as a leader and advocate for AI tooling within the data governance space - identifying opportunities to apply AI to automate governance workflows, improve data context, enhance trust scoring, and accelerate adoption of governance best practices across engineering teams.
- Collaborate Across Teams: Work closely with data engineers, analysts, and compliance officers to align data governance initiatives with business needs and regulatory requirements.
Requirements
- Experience: 5+ years in data engineering, data governance, or a related field, with hands-on experience in data classification, cataloging, quality assurance, and trust frameworks. Engineering ability to design and implement data governance and quality processes is critical to success.
- Trust & Quality Expertise: Demonstrated experience building data trust signals, quality scorecards, or similar frameworks that make data reliability visible and actionable for both engineers and non-technical stakeholders.
- Programming Experience: Proficiency in Python or a comparable programming language, and experience building scalable data tooling or automation pipelines.
- Technical Proficiency: Strong knowledge of data governance tools and platforms, and experience with cloud data warehouses like Snowflake. Experience with data catalog platforms and driving adoption across engineering organizations is a strong plus.
- Bonus: Compliance Knowledge: Familiarity with SOX, CCPA, and other data privacy and financial regulations, and ability to apply technical skills to governance practices that meet audit and compliance requirements.
Compensation
Base salary: $160,000 - $221,000, plus bonus, equity, and benefits. Actual offer may vary based on location, skills, qualifications, and experience.
Skills
Python, Terraform, Snowflake, Data Catalog, Data Lineage, Metadata Management, Data Quality, SOX Compliance, AI Tools, Cloud Data Warehouses
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