Senior Analytics Engineer

Plaid
United States
HybridCareer-pivot friendly

Who this role is best for

Best suited to mid-level analytics engineers with marketing analytics experience who thrive in full-stack data modeling and predictive analytics.

Best fit for

  • Marketing analytics specialists with SaaS or usage-based tech experience
    — “Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company”
  • Data modelers comfortable owning semantic layers and activation pipelines
    — “Own the dbt models and data marts that power Marketing analytics, activation, and reporting”
  • Applied data scientists who bridge analytics engineering and predictive modeling
    — “In addition to core analytics engineering, you’ll work on predictive modeling, experimentation, lifetime value (LTV), and attribution”

Things to consider

  • Production-grade model deployment expected beyond exploratory analysis
    — “Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity)”

How to stand out

  • Showcase dbt modeling projects with documentation standards
    — “Enable self-serve analytics through AI tools and well-documented semantic models”
  • Demonstrate end-to-end ownership of marketing attribution frameworks
    — “Partner with Marketing leadership on measurement frameworks, experiment design, and spend optimization”
  • Highlight predictive model deployments with business impact metrics
    — “Demonstrated experience shipping predictive models or applied ML in a business context”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed and maintained dbt models for Marketing analytics
  • Built predictive models for lead scoring and LTV
Typical background
Data EngineeringAnalytics

Skills & requirements

Required

dbtPredictive ModelingData EngineeringSQL

Preferred

Ignition PerspectiveAI Tools

Stack & domain

PythonReactLeadershipCommunicationFinance

About the role

As an Analytics Engineer at Plaid, you'll be responsible for building and maintaining data models and predictive frameworks that empower marketing teams to make data-driven decisions, with a focus on enhancing financial product experiences and driving growth.

Original posting from Plaid via Ashby

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.

The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA and Marketing organizations. We build and maintain the core semantic layer data models (dbt on Databricks), activation layer, and BI surfaces that these teams rely on — and we partner with stakeholders to turn those models into decisions, forecasts, analytics and experiments.

As a Senior Analytics Engineer, you’ll also act as an applied data science partner. In addition to core analytics engineering, you’ll work on predictive modeling, experimentation, lifetime value (LTV), and attribution alongside the broader team.

As a Senior Analytics Engineer on the Marketing pod, you will be the technical owner of Plaid's Marketing data stack. You will build the dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses 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 — with a north star that aims for prescriptive and production-grade analytics. You'll also help build the AI-powered experiences that let Marketing partners self-serve from our metric layer

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)
  • 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

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.

Please review our Candidate Privacy Notice here https://plaid.com/legal/#candidate-privacy-notice.

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Source: Plaid careers (Ashby)

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