# Analytics Engineer

**Company:** [Plaid](https://hotfix.jobs/companies/plaid)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $157k – $215k/yr
**Experience:** 4+ years
**Skills:** SQL, dbt, Python, Databricks, Snowflake, BigQuery, Redshift, Predictive Modeling, Lead Scoring, Ltv, Channel Attribution, Data Modeling
**Posted:** 2026-04-29

> Builds and owns dbt models, predictive frameworks (LTV, lead scoring, attribution), and self-serve analytics tools for Marketing at a fintech SaaS company. Partners with leadership on experiments, spend optimization, and AI-powered experiences. Requires 4+ years experience, advanced SQL/Python, cloud warehouses.

## Job Description

## Responsibilities
- 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.

## Qualifications
- Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience).
- 4+ 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.

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