Director of Data Engineering




WorkStep is a data-first company, and putting data to work is an aspect of everything we do. Our growing Data team is a specialized, cross-functional group that collaborates with a variety of departments to help drive decisions and provide direction for the company. As Director of Data Engineering at WorkStep, you will be instrumental in continuing to build out our analytics and data pipeline capabilities in the short term and laying the foundations for sophisticated data science techniques in the long term. You will work directly with the CTO to recruit a strong bench of talent, expand our pipelines, model our vast data repositories, and develop mechanisms for bringing critical thinking to all corners of our business operations. The right candidate will have experience-based opinions on how we should collect, move, store, analyze, and leverage data, accelerating the way we deliver insights to our product and business operations.

Skills Required

SQL, R, Looker, Data Warehousing, Data Pipelines, Machine Learning


Remote Only

Remote Friendly?

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Other Engineering

Primary Function

Data Scientist

Type of Position

Full Time

Company Website

Duration of Contract

Shared By

Justin Butler

Relationship to Company

Hiring Manager / Company Representative

Additional Notes

WorkStep has grown from 12 to 50+ employees over the last year and we're ready to hire our first Data leader to head up, as well as double the size of our Data team in the next 9 months. This an opportunity to have a foundational role in a rocketship start-up team. WorkStep's mission is to provide transparency and mobility to the blue collar workforce, and we've gained more than a million members nationwide and continue to expand super fast. We've just closed our Series B only 12 months after our Series A, so we have a huge year of growth ahead of us. We have ETL processes in Python feeding a BigQuery warehouse, modeled with dbt and analyzed via Looker and Mode. We're currently laying groundwork for operationalizing and productionalizing machine learning models in our customer-facing features.

Added On

February 24, 2022
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