Senior Analytics Engineer
About The Position
Plaid’s Analytics Engineering team owns the full-stack analytics foundation for its GTM, CGX, NEA, and Marketing organizations. The team builds and maintains core semantic-layer data models using dbt on Databricks, activation layers, and BI surfaces, and partners with stakeholders to turn models into decisions, forecasts, analytics, and experiments. The Senior Analytics Engineer on the Marketing pod is the technical owner of Plaid’s Marketing data stack. The role builds dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses to plan spend, measure performance, and drive growth. It also partners with PMM, Growth Marketing, and Marketing leadership on core data models, frameworks, and tools such as lifetime value (LTV), lead scoring, and experimentation tooling, with a focus on prescriptive, production-grade analytics. The role contributes to AI-powered experiences that enable Marketing partners to self-serve from the metric layer and acts as an applied data science partner on predictive modeling, experimentation, LTV, and attribution.
Requirements
- Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Economics, or Engineering, or equivalent experience.
- At least 5 years of proven experience in analytics engineering, data science, or a closely adjacent function.
- Advanced SQL and production-grade data modeling experience; dbt is strongly preferred.
- Python proficiency for modeling and analysis work.
- Hands-on experience with a modern cloud warehouse such as Databricks, Snowflake, BigQuery, or Redshift.
- Demonstrated experience shipping predictive models or applied machine learning in a business context.
- Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company.
- Strong stakeholder communication skills and ability to autonomously drive projects end-to-end.
Responsibilities
- Own the dbt models and data marts that power Marketing analytics, activation, and reporting.
- Build, validate, and productionize predictive models for lead scoring, LTV, channel attribution, and 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 data infrastructure for Marketing.
Benefits
- Comprehensive benefit plan, including medical, dental, vision, and 401(k).
- Equity and/or commission may be provided as additional compensation, depending on the position offered.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
