Senior Analytics Engineer

• The Analytics Engineering team owns the full-stack analytics foundation for Plaid’s GTM, CGX, NEA and Marketing organizations. We build and maintain the core semantic layer data models (dbt on Databricks), activation layer, and BI surfaces that these teams rely on — and we partner with stakeholders to turn those models into decisions, forecasts, analytics and experiments
• As an Analytics Engineer, you’ll also act as an applied data science partner. In addition to core analytics engineering, you’ll work on predictive modeling, experimentation, lifetime value (LTV), and attribution alongside the broader team
• As an Analytics Engineer on the Marketing pod, you will be the technical owner of Plaid’s Marketing data stack. You will build the dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses to plan spend, measure performance, and drive growth
• You’ll partner directly with PMM, Growth Marketing, and Marketing leadership to deliver core data models, frameworks, and tools — including LTV, lead scoring, and experimentation tooling — with a north star that aims for prescriptive and production-grade analytics. You’ll also help build the AI-powered experiences that let Marketing partners self-serve from our metric layer
• Own the dbt models and data marts that power Marketing analytics, activation, and reporting
• Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders
• Partner with Marketing leadership on measurement frameworks, experiment design, and spend optimization — translating business questions into analytical answers
• Enable self-serve analytics through AI tools and well-documented semantic models
• Collaborate with ML, Data Engineering, and Ops teams to deliver best-in-class data infrastructure to Marketing

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft
• Advanced SQL and production-grade data modeling experience — dbt strongly preferred
• Strong stakeholder communication and the ability to autonomously drive projects end-to-end
• 4+ years of proven experience in analytics engineering, data science, or a closely adjacent function
• Python proficiency for modeling and analysis work
• Demonstrated experience shipping predictive models or applied ML in a business context
• Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)
• Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company
• Bachelor’s degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)
• We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn’t fully match the job description