Staff Data Engineer

Front is the customer operations platform built for B2B complexity, keeping every team, tool, and customer conversation in sync so companies can scale without losing connection. Others handle simple interactions. Front handles the coordination and context behind complex B2B customer relationships. Over 9,000 companies, including Uber Freight, Navan, and Stripe, rely on Front because it's the only one that can run the operational layer that makes customer-facing work actually succeed.

Backed by Sequoia Capital and Salesforce Ventures, Front has raised $204M from leading venture capital firms and independent investors including top executives at Atlassian, Okta, Qualtrics, Zoom, and PagerDuty. Front has received numerous Great Place to Work accolades, including Built In's 100 Best Midsize Places to Work in SF 2025, Top Places to Work by USA Today 2025, Y Combinator's list of Top Companies in 2023, #4 on Fortune’s Best Workplaces in the Bay Area™ ,Inc. Magazine's 2022 Best Workplaces list, and Forbes Best Startup Employers 2022 List.

Front’s Data team builds the analytics infrastructure that powers decision-making across the company — from product insights to GTM performance. We’re looking for a Staff Data Engineer to own critical parts of that platform end-to-end: designing scalable pipelines and data models, raising the bar on reliability and data quality, and enabling self-serve data access for teams across Front.

This is a high-impact role for someone who loves turning complex, messy inputs into trusted datasets, and who can partner closely with analysts, data scientists, and product stakeholders to deliver data systems that are fast, secure, and built to last. You’ll thrive here if you’re hands-on, pragmatic, and excited to set technical direction while still shipping.

• Architect data pipelines that provide fast, optimized, and robust end-to-end solutions for internal users of the analytics infrastructure

• Automate manual processes and create a platform in favor of self-service data consumption

• Own the quality of our analytics data and ensure the Data Team’s SLAs are met on a timely basis

• Design data schemas and fine-tune queries around large, complex data sets

• Interface with data scientists, analysts, and non-data stakeholders to understand their needs and promote best data practices

• Keep our data available and secure across multiple data centers and regions

• Implement a robust monitoring & logging framework that guarantees traceability and audibility

• Vet tools and technologies for the most viable solution for each problem at hand, and manage tools and data vendors involved

• Bring strong AI fluency to how you build and operate — using AI tools thoughtfully to accelerate development, improve quality, and unlock new approaches to data reliability and automation

• BS/BA in Computer Science, Mathematics, or a relevant technical field (or equivalent practical experience)

• At least 5 years of experience as a Data Engineer, or in a role with deep ETL expertise

• Experience managing a Snowflake data warehouse

• Strong programming fundamentals, with an ability to write modular, maintainable code

• Advanced SQL and Python skills and strong comfort working with large datasets

• Working knowledge of at least one big data technology (HDFS, EMR, Redshift, Spark, Flink, or Presto)

• Experience with workflow management tools (preferably Airflow)

• A proactive, service-oriented mindset with a “can-do” approach and positive attitude

• Strong ability to manage multiple projects/tasks across multiple stakeholders