Job Overview
Location
San Francisco
Job Type
Full-time
Category
Data Engineer
Date Posted
March 28, 2026
Full Job Description
đź“‹ Description
- • Senior Data Engineer at WorkWhile Inc. will lead the development and operation of the data platform that powers analytics, machine learning models, and operational intelligence across the staffing marketplace, directly enabling better worker-business matches and improved marketplace dynamics.
- • Design, build, and maintain scalable data pipelines and infrastructure on Google Cloud Platform, including Dagster-based orchestration, BigQuery data warehouse, and integrations between PostgreSQL production systems and analytical layers, ensuring high-quality, reliable data is available for data science, product, and operations teams.
- • Collaborate closely with Data Science, Product Engineering, and Operations to support ML model training and deployment, optimize data warehouse performance, enable reverse ETL workflows, and ensure clean datasets are available for self-serve analytics and reporting.
- • Work in a fast-paced, mission-driven environment where contributions directly impact WorkWhile’s goal to make hourly work more accessible, reliable, and rewarding by improving shift matching, demand forecasting, worker reliability prediction, and dynamic pricing.
- • Own and evolve the data platform with a focus on reliability, observability, and code quality, including Terraform-managed GCP infrastructure, Cloud Tasks and Cloud Scheduler optimization, and data quality monitoring, while mentoring best practices in pipeline development and testing.
- • Drive improvements in data architecture through dataset organization, table design, partitioning, clustering, and query optimization in BigQuery, ensuring cost-effective and performant analytical workloads across the organization.
- • Partner with engineering teams to implement infrastructure-as-code and containerized deployments, supporting scalable and repeatable data workflows that align with DevOps and cloud-native principles.
🎯 Requirements
- • Bachelor’s degree in Computer Science, Data Engineering, Mathematics, or equivalent experience
- • 5+ years in data engineering or data platform engineering
- • Expertise in SQL, with the ability to write and optimize complex analytical queries across BigQuery and PostgreSQL
- • Proficiency building data pipelines in Python
- • Experience with Dagster or similar orchestration tools (Airflow, Prefect)
- • Experience maintaining data warehouses on BigQuery, Snowflake, or Redshift
- • Hands-on experience with Google Cloud Platform services
- • Experience with infrastructure-as-code (Terraform) and containerized deployments (Docker, ECS, Cloud Run, Kubernetes, etc.)
- • Proficiency with data quality frameworks, monitoring, and observability tooling
- • Strong collaboration skills and a track record of partnering effectively with Data Science and Product Engineering teams
🏖️ Benefits
- • Remote-friendly work culture with office hubs in SF, NY, Seattle & Toronto
- • Medical, dental, & vision coverage
- • Flexible time off
- • 401(k) with employer match
- • WFH stipend to support your home office needs
- • In-person company offsites
Skills & Technologies
About WorkWhile Inc.
WorkWhile is a labor marketplace that uses predictive algorithms to match hourly workers with shifts offered by logistics, warehousing, hospitality, and retail employers across the United States. The platform vets applicants through background checks and skills assessments, then schedules them for shifts that fit their availability and pay preferences. Employers access a pool of pre-qualified workers on demand, while workers gain flexible hours, next-day pay, and benefits such as telemedicine and gas discounts. Founded in 2019, WorkWhile operates primarily in California and Texas, facilitating thousands of daily shift placements for both national brands and local businesses.
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