The Senior Data Analyst will build and maintain audit-ready data pipelines, validation, monitoring, and governance processes while coordinating technical responses to audit requests. The role requires 7+ years in data analytics or engineering, strong SQL and Python, and production experience with dbt, Airflow, and regulated data environments.
110k – 211k/yr
Remote7+ YOEData Analytics
About the role
Responsibilities
Collaborate on the technical coordination and stewardship layer for shared datasets and systems in scope for audit, including financial systems, recordkeeping, and downstream reporting processes.
Improve governance, communication, and coordination around upstream schema and logic changes that impact downstream systems and audit-related processes.
Support technical analysis and downstream impact assessment during change management for datasets, tables, and systems in scope for audit.
Develop and maintain reusable audit-ready dataset patterns, including automated validation, data quality checks, and monitoring.
Review audit-scoped processes and datasets, identify operational pain points, and propose reengineering and longer-term process improvements.
Provide technical guidance to business stakeholders and the Audit Project Manager on audit requests.
Requirements
7+ years of experience in data analytics or data engineering, ideally supporting internal audit, risk, or SOX compliance functions in fintech, payments, financial markets, or crypto.
Experience managing and designing data architecture in a regulated environment, including pipelines built with governance, traceability, and audit requirements from the outset.
Hands-on experience building and owning production data pipelines.
Strong familiarity with dbt and Airflow or equivalent orchestration tools.
Mastery of SQL, including complex joins, common table expressions, and analytical functions.
Strong Python proficiency for pipeline development and analysis.
Experience documenting technical and business requirements, including metadata, KPI definitions, business rules, data process flows, and data dictionaries.
Familiarity with data administration tasks such as job scheduling, error and exception handling, and troubleshooting production ETL workflows.
Experience partnering with Data Engineering or Data Governance teams on shared datasets, schema changes, and downstream impact analysis.
Strong communication skills, with the ability to translate audit and business requirements into technical specifications and explain technical work to non-technical stakeholders.
Nice to Have
Experience building or scaling a data analytics function within an audit or risk organization.
Familiarity with AI-assisted or automation tools for data quality checks, testing, or workflow efficiency.
Familiarity with audit management platforms such as AuditBoard, Jira, or Workiva.
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