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Plaid is a fintech infrastructure company that powers financial connectivity for millions of users and thousands of developers. The Analytics Engineering team owns the full-stack analytics foundation for Plaid's go-to-market, customer experience, and marketing organizations, building and maintaining core semantic layer data models (dbt on Databricks), activation layers, and BI surfaces.
As a Senior Analytics Engineer on the Marketing pod, you will be the technical owner of Plaid's Marketing data stack. You'll build dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses to plan spend, measure performance, and drive growth. This role combines core analytics engineering with applied data science responsibilities.
Key responsibilities include:
- Owning dbt models and data marts that power Marketing analytics, activation, and reporting
- Building, validating, and productionizing predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders
- Partnering with Marketing leadership on measurement frameworks, experiment design, and spend optimization
- Enabling self-serve analytics through AI tools and well-documented semantic models
- Collaborating with ML, Data Engineering, and Ops teams to deliver best-in-class data infrastructure
You'll work directly with PMM, Growth Marketing, and Marketing leadership to deliver core data models, frameworks, and tools with a north star of prescriptive, production-grade analytics. You'll also help build AI-powered experiences that let Marketing partners self-serve from the metric layer.
Qualifications:
- Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)
- 5+ years of proven experience in analytics engineering, data science, or closely adjacent function
- Advanced SQL and production-grade data modeling experience (dbt strongly preferred)
- Python proficiency for modeling and analysis work
- Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)
- Demonstrated experience shipping predictive models or applied ML in a business context
- Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company
- Strong stakeholder communication and ability to autonomously drive projects end-to-end
