Note: The job is a remote job and is open to candidates in USA. Kraken is a leading crypto platform that has built a globally accessible financial infrastructure. The Sr. Data Analyst role focuses on ensuring audit readiness from a data standpoint, involving the ownership of data inventories, playbooks, and access processes to support internal audit functions.
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
- Spearhead improvements to 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 the change management process to improve downstream visibility for datasets, tables, and systems in scope for audit
- Support the development and maintenance of reusable audit-ready dataset patterns, including automated validation, data quality checks, and monitoring
- Review processes and datasets in scope for Audit, examine existing operational pain points, and propose reengineering opportunities and longer-term process improvements
- Provide technical guidance to business stakeholders and the Audit PM around specific Audit requests
Skills
- 7+ years of experience in data analytics or data engineering, ideally supporting internal audit, risk, or SOX compliance functions within the fintech, payments, financial market or crypto where data quality and scale are non-negotiable
- Experience managing and designing data architecture in a regulated environment, having designed and built data pipelines with governance, traceability, and audit requirements considered from the outset
- Hands-on experience building and owning production data pipelines, with strong familiarity with dbt and Airflow or equivalent orchestration tools
- Full mastery of SQL including complex joins, CTEs and analytical functions, alongside 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: job scheduling, error/exception handling, and troubleshooting production ETL workflows
- Experience partnering with Data Engineering and/or Data Governance teams on shared datasets, schema changes, and downstream impact analysis
- Strong communicator who can translate audit and business requirements into technical specifications and translate technical work back into terms non-technical stakeholders understand
- Experience building or scaling a data analytics function within an audit or risk organization from the ground up
- Familiarity with AI-assisted or automation tools for data quality checks, testing, or workflow efficiency
- Familiarity with audit management platforms (e.g., AuditBoard, Jira, Workiva)
Company Overview
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