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Data Engineer - Finance

Bellevue, Washington, United States

Pay
$60–85/hour — pay source
This role is for one of our clients Compensation: $60 - $85 per hour A rapidly growing AI organization is seeking a Data Engineer — Finance to build and maintain the data infrastructure that powers its finance operations. You'll join a lean, high-impact team responsible for developing scalable data pipelines, improving data quality, and supporting critical financial initiatives. This is a 6-month, full-time onsite contract with the possibility of extension based on performance and business needs.
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Work setup
Unconfirmed
Employment
Full-time — employment source
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.
Read the full posting
Apply at Weekday AI

What you’ll work on

Full posting
  • 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.

From the employer’s posting
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.
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.
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.

What you’ll bring

All qualifications

Core experience

  • 2–4 years of professional experience as a Data Engineer.
  • 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.

Preferred experience

  • Experience supporting finance, accounting, or enterprise business data platforms.
  • Familiarity with cloud-based data infrastructure and modern data engineering best practices.
  • Experience working in fast-paced, high-growth technology environments.
Qualification wording
2–4 years of professional experience as a Data Engineer.
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.
Experience supporting finance, accounting, or enterprise business data platforms.
Familiarity with cloud-based data infrastructure and modern data engineering best practices.
Experience working in fast-paced, high-growth technology environments.

Tools in this posting

  • SQL
  • PySpark
Source — Tool mentions in context
- 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.
- 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.
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.
- 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.

Job description

View original posting ↗

This role is for one of our clients

Compensation: $60 - $85 per hour

A rapidly growing AI organization is seeking a Data Engineer — Finance to build and maintain the data infrastructure that powers its finance operations. You'll join a lean, high-impact team responsible for developing scalable data pipelines, improving data quality, and supporting critical financial initiatives. This is a 6-month, full-time onsite contract with the possibility of extension based on performance and business needs.

Location: Onsite – San Francisco, CA / New York, NY / Bellevue, WA

Requirements

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.

Role Details

  • 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.

Equal Opportunity

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

Contract & Payment Terms

  • 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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

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Source & posting history

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Pay
This role is for one of our clients Compensation: $60 - $85 per hour A rapidly growing AI organization is seeking a Data Engineer — Finance to build and maintain the data infrastructure that powers its finance operations. You'll join a lean, high-impact team responsible for developing scalable data pipelines, improving data quality, and supporting critical financial initiatives. This is a 6-month, full-time onsite contract with the possibility of extension based on performance and business needs.
Location & working pattern

Bellevue, Washington, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization

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Status in our records
Active
First seen by us
Aug 15, 2026
Recorded sightings
172
Last seen by us
Oct 9, 2026
Employer says posted
Jul 29, 2026

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