Senior Data Engineer

Role overview

Build and maintain the data pipelines and models that turn complex source data into reliable datasets for reporting and business decisions. You’ll own the modeling layer between application systems and analytics teams, working across functions to make data accurate, useful, secure, and easier to trust.

Responsibilities

- Design production data pipelines and scalable models for analytics and enterprise reporting. - Establish validation, testing, and quality practices to improve the accuracy and reliability of datasets. - Partner with application engineers to understand source systems and shape downstream data capture and modeling. - Work with analytics, business intelligence, and business teams to translate reporting needs into reusable datasets. - Apply access controls and monitoring to support privacy and regulatory requirements, including GDPR, CCPA, and GLBA. - Mentor data engineers on modeling, documentation, and data processing practices; use AI-assisted tools where they improve engineering work.

Requirements

- At least four years of experience in data engineering, analytics engineering, or dimensional modeling. - Experience building production data solutions and modeling data for downstream reporting. - Ability to work with engineering and business partners to clarify data needs and deliver trusted datasets. - Sound judgment around data quality, security, and privacy controls. - Ability to document practices and support the development of other engineers.

Benefits and work setup

- Remote-first arrangement, with eligible locations limited to specified U.S. states; Ontario is the only eligible location for remote technical roles in Canada. - Offices are available in Chicago and St. Petersburg for team collaboration.