Analytics Engineer

Role Overview

Join Plaid’s Analytics Engineering team as an Analytics Engineer. You’ll be the technical owner of Plaid’s Marketing data stack, responsible for building the foundations that power Marketing analytics, activation, and reporting.

Responsibilities

• Own Plaid Marketing analytics assets: dbt models and data marts that power Marketing analytics and reporting.
• Build and productionize predictive models in partnership with Marketing and GTM stakeholders, including:
  • Lead scoring
  • LTV (Lifetime Value)
  • Channel attribution
  • Propensity models
• Collaborate with Marketing leadership to create measurement frameworks, support experiment design, and drive spend optimization by translating business questions into analytical outputs.
• Work cross-functionally with ML, Data Engineering, and Ops teams to deliver production-grade data infrastructure for Marketing.
• Enable self-serve analytics via AI tools and well-documented semantic models.

Requirements

• Demonstrated experience shipping predictive models or applying ML in a business context.
• Hands-on experience with a modern cloud data warehouse (e.g., Databricks, Snowflake, BigQuery, or Redshift).
• Python proficiency for modeling and analysis.
• Strong stakeholder communication and ability to drive projects end-to-end.
• Bachelor’s degree in a quantitative field (CS, Statistics, Economics, Engineering) or equivalent experience.
• Advanced SQL and production-grade data modeling experience.
• dbt strongly preferred.
• 4+ years of proven experience in analytics engineering, data science, or a closely adjacent function.

Nice to Haves

• Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company.