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Kraken, a leading crypto platform founded in 2011 and part of the Payward group, is seeking a Senior Data Analyst to join its Data & Audit Readiness team. This role focuses on building and maintaining audit-ready data infrastructure, pipelines, and governance frameworks that support internal audit, risk, and compliance functions across the organization.
You will own the inventories, playbooks, catalogs, and access processes that keep data systems audit-ready, translating audit engagements into coordinated, well-documented technical responses. This is a hands-on builder role requiring a data architect's background—someone who has designed and built production data pipelines and understands how to shape them for traceability, access control, and testability from inception.
Key responsibilities include:
- Collaborating on technical coordination and stewardship for shared datasets and systems in scope for audit, including financial systems, recordkeeping, and downstream reporting
- Spearheading improvements to governance, communication, and coordination around upstream schema and logic changes impacting downstream audit processes
- Supporting technical analysis and downstream impact assessment during change management to improve visibility for audit-scoped datasets and systems
- Developing and maintaining reusable audit-ready dataset patterns with automated validation, data quality checks, and monitoring
- Reviewing audit-scoped processes and datasets, identifying operational pain points, and proposing process improvements
- Providing technical guidance to business stakeholders and audit leadership on specific requests
Required qualifications include 7+ years in data analytics or data engineering, ideally supporting audit, risk, or SOX compliance in fintech, payments, or crypto. You must have hands-on experience designing data architecture in regulated environments, building production pipelines with dbt and Airflow (or equivalent), mastery of SQL and Python, and strong documentation skills. Experience partnering with data engineering and governance teams on shared datasets and schema changes is essential. You should be a strong communicator who can translate between technical and non-technical stakeholders.
Nice-to-have skills include experience building or scaling a data analytics function within audit/risk organizations, familiarity with AI-assisted data quality tools, and experience with audit management platforms like AuditBoard or Workiva.
