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Kraken, a leading crypto trading platform founded in 2011, is seeking a Senior Data Analyst to join its Data & Audit Readiness team. This role sits within Payward's broader data infrastructure organization and focuses on ensuring the company's data systems and datasets are audit-ready and compliant with regulatory requirements.
You will own the inventories, playbooks, catalogs, and access processes that maintain audit readiness across the data platform. This is a hands-on, builder-focused position requiring a data architect's background—someone who has designed and built production data pipelines and understands how to architect for traceability, access control, and testability from inception.
Key responsibilities include:
- Collaborating on technical coordination and stewardship of 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 that impact 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 to identify operational pain points and propose reengineering opportunities
- Providing technical guidance to business stakeholders and audit teams on specific requests
Required qualifications:
- 7+ years in data analytics or data engineering, ideally supporting internal audit, risk, or SOX compliance in fintech, payments, or crypto
- Experience designing data architecture in regulated environments with governance and audit requirements built in from the start
- Hands-on production experience with dbt, Airflow, or equivalent orchestration tools
- Advanced SQL proficiency (complex joins, CTEs, analytical functions) and strong Python skills
- Experience documenting technical and business requirements: metadata, KPI definitions, business rules, data flows, and data dictionaries
- Familiarity with data administration: job scheduling, error handling, and ETL troubleshooting
- Experience partnering with Data Engineering and Data Governance teams on shared datasets and impact analysis
- Strong communication skills translating between audit/business requirements and technical specifications
Nice-to-haves 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.
