Senior Data Engineer

Who you are

• 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 (we use Estuary), workflow orchestration (we use Astronomer Airflow), transformations (we use dbt), and BI tools with semantic layers (we use Holistics)
• Strong SQL and data modeling foundations for clean, well-structured models that others can build on and maintain
• Experience owning data quality end-to-end, including testing and observability frameworks infrastructure and tools with a genuine bias for reliability
• AI-native chops: you productively integrate AI into your development workflows to build with curiosity and strong opinions loosely held
• Proven ability to take accountability for systems and themes, not just individual tasks or projects. You see the work through and communicate clearly along the way
• Ability to collaborate cross functionally with data analysts, product engineers, and non-technical stakeholders, bringing clarity to ambiguity
• Experience differentiators: marketplace or transaction-platform data, applied AI/ML pipeline work, customer-facing analytics products, food and beverage or CPG domain knowledge, experience integrating LLM tooling into data workflows
• Please note that applicants should be authorized to work in the United States. Though we are interested in every qualified candidate, we are unable to offer visa sponsorship at this time

What the job involves

• 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 in our data tools, ensuring accuracy, consistency, and documentation
• Design and enforce data quality standards across the stack, defining what trusted data means at Spoiler Alert and developing the monitoring and testing that upholds it
• Make intentional architectural decisions with the appropriate level of abstraction, documenting decisions and tradeoffs so the team can build confidently on your work, including data infrastructure for effective product applications of AI/ML
• 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, and drive root cause work that prevents them from recurring
• Contribute to shared support responsibilities and help build a culture of reliability across the data platform
• Take end-to-end accountability for data systems and roadmap themes, owning projects through from design to production to iteration, communicating tradeoffs and risks along the way
• Partner with Product, Data, and Engineering teammates to ensure our pipelines, models, and tooling support reliable internal and external decision making using our data
• Identify opportunities where better data infrastructure creates leverage for Product, Data, Engineering, and Operations teams, and advocate for those investments with clarity
• Contribute meaningfully to architecture conversations and Engineering reflection, shaping technical decisions with your expertise

Benefits

• Stock option packages
• 20 vacation days and 10 sick days per year
• Subsidized health, dental and vision insurance
• Life insurance and paid family and medical leave
• Paid volunteer outings and civic engagement leave
• Pre-tax 401(k) and post-tax Roth 401(k) options
• Environmentally-friendly 401k fund option
• Learning & career development stipends
• Up to 16 weeks of paid parental leave
• $500 FSA employer contribution
• 17 company holidays, including an EOY rest week
• Remote first work environment
• Home office stipend