Business Intelligence

San Francisco
Engineering – Engineering /
Full-time /
Hybrid
We are the Business Intelligence team, a full-stack analytics engineering team that owns the data pipeline from foundational data to trusted dashboards across Product, Marketing, and Go-To-Market (GTM) at Plaid. Our aim is to create the infrastructure, data models, and self-serve systems that enable stakeholders to confidently make decisions based on reliable, accessible data.

As a member of Business Intelligence working directly with our Network Enablement product team, you will be at the forefront of building scalable and reliable analytics foundations that power decision-making across Product, Engineering, and Data Science. This senior individual contributor role is focused on developing foundational product-data infrastructure, defining and maintaining trusted metrics, and enabling self-serve analytics and AI tooling.

Responsibilities

    • Build and maintain foundational dbt models and curated, source-of-truth datasets that support analytics, experimentation, and decision-making across Product, Engineering, and Data Science.

    • Collaborate with Product Managers, Engineers, and Data Scientists to translate instrumentation and analytical requirements into well-structured data models.

    • Develop and enforce standards for metrics, modeling practices, and documentation to ensure consistency and reusability.

    • Own the full analytics engineering lifecycle—from raw ingestion and transformation to surfacing insights in BI tools like Tableau or Mode.

    • Partner with Data Science teams to enable experimentation, forecasting, and AI tooling with reliable, structured data.

    • Partner with Data Engineering to ensure data quality and observability, including testing, alerting, and documentation.

    • Enable self-serve analytics by building semantic layers and reusable data products that empower teams to independently access trusted insights.

    • Act as a technical thought partner within the product data domain, contributing to roadmap planning and data architecture decisions.


    • Impact:

    • Unlock insights by ensuring Data Science has clean, structured, and trustworthy data.

    • Reduce engineering and analytics rework by creating centralized and well-documented metrics.

    • Accelerate product iteration cycles by enabling Product teams to self-serve key usage and performance metrics.

    • Improve confidence and consistency in decision-making through robust, well-governed data systems.

Qualificaitons

    • 10+ years of experience in analytics engineering, data engineering, or a related technical data role.

    • Deep expertise with SQL and dbt, including modular modeling, documentation, and testing.

    • Proven track record of building source-of-truth data models that support product use cases.

    • Experience with cloud data warehouses (e.g., Databricks, Snowflake, Redshift, or BigQuery), semantic layers (dbt), version control (Git), and visualization tools (Tableau, Looker).

    • Familiarity with instrumentation design and working with product logs or event data.

    • Experience partnering with Product, Engineering, and Data Science stakeholders to translate business logic into technical data solutions.

    • Strong focus on data quality, governance, and scalability in analytics workflows.

    • Clear, concise communication skills and a collaborative, systems-oriented mindset.
$159,600 - $260,400 a year
The target base salary for this position ranges from $159,600/year to $260,400/year [in Zone 1, in Zone 4 or encompassing all Zones]. The target base salary will vary based on the job's location. 

Our geographic zones are as follows:
Zone 1 - New York City and San Francisco Bay Area 
Zone 2 - Los Angeles, Seattle, Washington D.C.
Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego
Zone 4 - Raleigh-Durham and all other US cities

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.