Principal Data Engineer

Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth. The Principal Data Engineer will own the analytics data architecture, partnering with various teams to ensure data integrity and facilitate business decisions across the company.

Responsibilities:

• Database Architecture. You own our data warehouse and the reporting layer on top of it, setting patterns for how data is modeled, evolved, and exposed
• Analytics Engineering. You write SQL and dbt models, refactor transformations, and build the tables and views downstream teams rely on
• Cross-Functional Partnership. You proactively engage with teams across the company to understand how data is created and used, identify gaps, and guide solutions. You’re the connective tissue between product engineering, architecture, analytics, and the business stakeholders who depend on our data
• Platform Architecture. You partner with our DevX and architecture teams on the boundary between product engineering services and Snowflake, including leading efforts to automate schema propagation so changes upstream flow cleanly into the warehouse without manual intervention
• Data Quality. You build models, tests, and processes that anticipate malformed data and upstream changes, making our pipelines boring to operate
• Observability & Reliability. You instrument what you own, define meaningful SLOs and data quality checks, and participate in our rotating on-call schedule (light volume, mostly responding to issues as they come in)
• Ingestion & Integration Jobs. You own and extend our Python jobs running on Glue, Lambda, and Step Functions — primarily ingesting data from third-party APIs, with a smaller set that pushes data out to downstream systems. The infrastructure for these jobs is managed in AWS CDK
• Mentorship & Technical Leadership. You pair with more junior engineers on real work, raise the bar on PR and architecture reviews, and define the patterns and standards the team writes against. You bring a systems-thinking lens and clear communication to every conversation, connecting what’s happening upstream in product engineering to what stakeholders need downstream

Requirements:

• 10+ years in Data Engineering, Analytics Engineering, or related fields, operating at a Principal or equivalent level
• Deep relational database architecture and data modeling expertise
• Expert-level Snowflake and SQL, with experience owning a warehouse at scale
• Strong analytics engineering experience, ideally with dbt
• Solid hands-on Python, with experience building data jobs on AWS Glue, Lambda, and Step Functions, and managing that infrastructure in AWS CDK
• Experience integrating with third-party APIs in both directions, including rate limits, retries, authentication, and idempotency
• Track record of building observable, reliable data systems
• Demonstrated technical leadership and mentorship with strong communication, systems thinking, and a track record of engaging stakeholders across an organization to drive cross-functional outcomes