Data Engineer - Finance

Key Responsibilities

• 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.

Requirements

• 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.

Preferred Qualifications

• 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.

Compensation

$60 - $85 per hour

Location

Onsite - 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.