Staff Data Engineer

TL;DR

Staff Data Engineer: Drive design and implementation of foundational data products and analytics platform capabilities powering critical product and business use cases with an accent on scalable patterns, orchestration, and cross-functional leadership. Focus on architecting extensible data modeling, leading platform evolution projects like Snowflake Semantic Views migration, and elevating data work quality across teams.

Location: Hybrid required if based in Washington D.C., Austin, Chicago, or NYC metropolitan regions; location flexibility otherwise.

Salary: $215,000 – $250,000 + equity + benefits

Company

We transform brick-and-mortar commerce using online retail tech to deliver cashback to users and profitable customers to businesses, processing billions in commerce annually.

What you will do

• Design and deliver complex, domain-critical data products for analysts, data scientists, and product teams to enable new features, ML models, and decisions.
• Architect scalable patterns for data modeling, orchestration, and transformation balancing flexibility, reusability, and cost-efficiency.
• Own platform evolution projects like migrating to Snowflake Semantic Views, extending Cortex, or improving orchestration tooling.
• Lead technical planning and delivery across cross-functional teams, breaking down initiatives into scoped workstreams.
• Drive platform adoption, mentor engineers, build documentation and tooling, and raise analytics engineering standards.
• Influence engineering, product, data science, and business stakeholders to align on requirements and deliver end-to-end solutions.

Requirements

• 6+ years in data or analytics engineering owning complex, business-critical data systems end-to-end
• Deep expertise in SQL and Python for transforming, testing, and orchestrating large datasets
• Fluency with AWS, Snowflake, dbt, Dagster, and designing extensible team-wide patterns
• Experience breaking down ambiguous cross-functional problems and leading implementation
• Strong communication across engineers, analysts, product managers, and leaders
• Ability to balance business value, maintainability, and platform standards

Nice to have

• Experience supporting ML workflows like feature building or model monitoring
• DevOps practices (CI/CD for data), data governance, or FinOps
• Work in fast-growing startups or platform teams serving internal customers

Culture & Benefits

• Medical, dental, vision coverage from Day 1; 401(k); equity (ISOs)
• Unlimited PTO + 10 federal holidays + week-long Winter Break
• Family planning + paid parental leave; fitness/wellness memberships; mental health support
• Learning & Development stipend; lunch reimbursement for in-office; flexible work
• Transparent culture; Employee Resource Groups; thoughtful team staffing for growth