# Senior Data Analyst, Data & Audit Readiness

**Company:** [Kraken](https://hotfix.jobs/companies/kraken)
**Location:** Remote
**Role:** Data Analytics
**Experience:** 7+ years
**Skills:** SQL, Python, dbt, Apache Airflow, ETL, Data Pipelines, Data Architecture, Data Governance, Data Quality, Data Modeling, Data Dictionaries, Kpi Definitions, Auditboard, Jira, Workiva
**Posted:** 2026-08-04

> Own audit-readiness data inventories, governance processes, pipelines, dashboards, and validation controls for shared financial and operational datasets. The role requires 7+ years in data analytics or engineering, production pipeline experience, advanced SQL and Python, and familiarity with dbt, Airflow, and regulated environments.

## Job Description

## 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 affect downstream systems and audit-related processes.
- Perform technical analysis and downstream impact assessments 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-scope 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.
- Advanced SQL skills, including complex joins, common table expressions, and analytical functions.
- Strong Python proficiency for pipeline development and analysis.
- Experience documenting technical and business requirements, 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, including translating audit and business requirements into technical specifications and explaining 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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