Senior Data Engineer - Spoiler Alert

About Spoiler Alert

Spoiler Alert is a CPG and retail tech company on a mission to expand consumer access to affordable, everyday essentials by unlocking the value in surplus inventory. We've powered the sale of over $6 billion of inventory from leading CPG brands like Unilever, Kraft Heinz, and Mondelez into hundreds of value channel retailers and wholesalers — recovering value for brands, reducing waste, and creating savings for consumers.

Role

We're hiring a Senior Data Engineer to build and own the data infrastructure that powers Spoiler Alert's next chapter. Our platform generates unique data across every supplier and buyer transaction, and how well we move, model, and make that data accessible determines our company’s ability to produce results for our industry. Decision intelligence, AI-powered pricing recommendations, demand matching, and customer-facing analytics will all run on the foundation this role helps build.

This is a hands-on technical leadership role for someone who takes ownership of systems end-to-end and sets the bar for the team around them. You'll work at the intersection of data, product, and platform engineering, partnering closely with Data and Product teams to make our data reliable, accessible, and useful.

Responsibilities

Build & Own the Data Platform

• Architect, build, and maintain the infrastructure that moves and transforms Spoiler Alert's marketplace data reliably and at scale, effectively incorporating AI coding tools to build with quality and velocity.
• Own the analytical schema in our data warehouse that serves internal analytics, aggregate analytics, and customer-facing reporting, ensuring accuracy, consistency, and documentation.
• Design and enforce data quality standards across the stack, defining what trusted data means at Spoiler Alert and developing monitoring and testing.
• Make intentional architectural decisions with appropriate abstraction, documenting tradeoffs so the team can build confidently on your work.

Raise the Bar for Engineering Quality

• Contribute exemplary code in pipeline logic, SQL, and data modeling that other engineers learn from and build on.
• Share meaningful code reviews that evolve our team's patterns and practices.
• Debug and resolve data issues quickly, driving root cause work that prevents recurrences.
• Contribute to shared support responsibilities and help build a culture of reliability across the data platform.

Lead Technically Across the Team

• Take end-to-end accountability for data systems and roadmap themes, owning projects through from design to production.
• Partner with Product, Data, and Engineering teammates to ensure our pipelines, models, and tooling support reliable internal and external decision-making.
• Identify opportunities where better data infrastructure creates leverage for Product, Data, Engineering, and Operations teams.
• Contribute meaningfully to architecture conversations and engineering reflections.

Qualifications

• 5–8+ years of data engineering experience, ideally at a B2B SaaS, marketplace, or data products company.
• Deep hands-on expertise across the modern data stack, including pipeline tooling (Estuary), workflow orchestration (Astronomer Airflow), transformations (dbt), and BI tools with semantic layers (Holistics).
• Strong SQL and data modeling foundations.
• Experience owning data quality end-to-end, including testing and observability frameworks.
• AI-native chops: productively integrate AI into your development workflows.
• Proven ability to take accountability for systems and themes, communicating clearly along the way.
• Ability to collaborate cross-functionally with data analysts, product engineers, and non-technical stakeholders.
• Experience differentiators: marketplace or transaction-platform data, applied AI/ML pipeline work, customer-facing analytics products, CPG domain knowledge.