Senior Analytics Engineer
Plaid offers a platform that enables applications to connect with users' bank accounts, facilitating a wide range of financial services. They provide tools for payments, personal finance management, credit, and more, serving clients like Moneybox, Western Union, and Affirm. Their core product is an API that provides access to a vast network of financial institutions, allowing developers to build financial products and services.
Funding
Projects
About Plaid
Plaid is a financial technology company that enables applications to connect with users' bank accounts. It allows consumers and businesses to interact with their bank accounts, check balances, and make payments through other financial technology applications. Plaid's network connects to over 12,000 financial institutions across 20 markets, serving a global user base of over 100 million. The company provides APIs for developers to build solutions for personal financial management, credit, payments, business finances, iGaming, and property management. Key products include Auth for account verification, Link for connecting accounts, Transactions for accessing financial data, Balance for real-time checks, Assets for verifying assets, and Identity for user verification. Plaid focuses on increasing conversion, fighting fraud, and providing clean, organized financial data for smarter underwriting and other financial services.
Skills
About the Role
You'll be the technical owner of Plaid's Marketing data stack, building dbt models, predictive frameworks, and self-serve data products that Marketing leadership relies on 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 — aiming for prescriptive and production-grade analytics. You'll also help build AI-powered experiences that let Marketing partners self-serve from the metric layer, acting as an applied data science partner working on predictive modeling, experimentation, lifetime value, and attribution.
Requirements
- 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 a 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 the 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 such as 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 best-in-class data infrastructure to Marketing
Benefits
- Medical, dental, vision insurance
- 401(k)
- Equity