Role OverviewA Data Engineer - Finance will build and maintain the data infrastructure that powers finance operations. The role is part of a lean, high-impact team responsible for developing scalable data pipelines, improving data quality, and supporting critical financial initiatives.
What You Will Do
Design, build, and maintain robust PySpark-based data pipelines, write and optimize complex SQL queries, collaborate with stakeholders, and own end-to-end data quality.
Why It Might Be a Fit
The ideal candidate has 2-4 years of experience as a Data Engineer, strong hands-on experience with PySpark, advanced SQL skills, and experience building large-scale ETL/data pipelines.
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
Benefits
- Hourly compensation: $60 - $85
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