Data Engineer - Finance

• 2–4 years of professional experience as a Data Engineer.
• Strong hands-on experience with PySpark and distributed data processing frameworks.
• Advanced SQL skills with experience writing efficient, production-grade queries.
• Experience building, maintaining, and optimizing large-scale ETL/data pipelines.
• Ability to work independently while collaborating effectively across cross-functional teams.
• Bachelor's degree in Computer Science or a related technical discipline.
• Excellent written and verbal communication skills.
• Willingness to work onsite full-time.

• Experience supporting finance, accounting, or enterprise business data platforms.
• Familiarity with cloud-based data infrastructure and modern data engineering best practices.
• Strong analytical and problem-solving abilities with attention to data accuracy.
• Experience working in fast-paced, high-growth technology environments.

• → Design, build, and maintain robust PySpark-based data pipelines to ensure accurate and timely financial data processing.
• → Write, optimize, and troubleshoot complex SQL queries to extract, transform, and validate large-scale financial datasets.
• → Collaborate closely with finance and engineering stakeholders to translate business requirements into reliable data infrastructure solutions.
• → Own end-to-end data quality by identifying, investigating, and resolving pipeline issues efficiently.
• → Improve the reliability, scalability, and performance of data workflows supporting finance operations.
• → Contribute to architecture discussions and recommend best practices for data engineering and pipeline optimization.
• → Document workflows, data models, and engineering processes to ensure maintainability and knowledge sharing.

• Employment Type: Independent Contractor
• Duration: 6-month contract with potential extension
• Work Arrangement: Full-time, Onsite
• Locations: San Francisco, CA / New York, NY / Bellevue, WA

Note: This is a hands-on data engineering position focused on building and maintaining production data infrastructure. It is not a business intelligence, reporting, dashboarding, machine learning, or AI research role.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

• You will be engaged as an independent contractor.
• This is a full-time onsite engagement.
• Projects may be extended, shortened, or concluded early based on business needs and performance.
• Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
• Payments are made weekly via Stripe or Wise based on services rendered.
• Please note: We are unable to support H1-B or STEM OPT candidates at this time.