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Data Governance Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Chime
Full Time position
Listed on 2026-06-26
Job specializations:
  • IT/Tech
    Data Engineering, Data Security, Data Analyst
Salary/Wage Range or Industry Benchmark: 160000 - 221000 USD Yearly USD 160000.00 221000.00 YEAR
Job Description & How to Apply Below

About The Role

The Data Governance function is pivotal in ensuring the integrity, trustworthiness, and effective management of Chime’s data assets. Our mission is to establish and operationalize data governance frameworks that not only meet compliance requirements, but actively enable high‑confidence decision making across the company. As a Data Governance Engineer, you will develop and implement policies and tools for data quality, developer enablement, certified datasets, and governance automation – with a sharp focus on building trust signals and scorecards that help data consumers quickly understand and act on the reliability of Chime’s data.

This is a hands‑on engineering role. You will write production‑quality code to build automation for governance and data quality processes using Terraform, Python, and contribute to internal libraries, frameworks, and orchestration workflows that enable scalable governance.

Key Responsibilities
  • Partner closely with data engineering, analytics, product engineering, and compliance teams to support Chime in data compliance and risk reduction initiatives, establish data quality as a product discipline, build trust signals and scorecards, implement governance workflows upstream, and ensure data context and metadata are sufficient for downstream use cases, including AI applications.
  • Review technical designs and implementation plans to provide guidance on appropriate development from a data governance and compliance perspective, acting as a trusted advisor to teams innovating at Chime.
  • Advocate for artificial intelligence tooling and adoption at Chime, identifying opportunities where AI adds leverage in data governance workflows.
  • Allocate time to strategic influence (40%), development and building (40%), and stakeholder management (20%).
  • 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.
  • 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 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, and usage guidance.
  • Automate governance processes:
    Deploy automation solutions for metadata management, data lineage tracking, access controls, and quality remediation workflows.
  • Champion SOX compliance:
    Ensure that data governance practices, controls, and audit trails meet regulatory requirements and are well documented.
  • Lead AI adoption for data governance:
    Identify 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:
    Align data governance initiatives with business needs and regulatory requirements.
Qualifications
  • 5+ years in data engineering, data governance, or a related field, with hands‑on experience in data classification, cataloging, quality assurance, and trust frameworks.
  • Demonstrated experience building data trust signals, quality scorecards, or similar frameworks that make data reliability visible and actionable.
  • Proficiency in Python or a comparable programming language, and experience building scalable data tooling or automation pipelines.
  • Strong curiosity and persistence in addressing ambiguous problems and delivering solutions.
  • Ability to navigate complex regulatory, business, and technical environments, breaking them into manageable pieces.
  • Excellent communication skills, able to write clear one‑pagers, run effective meetings, and translate technical concepts into plain language.
  • Produ…
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