Staff Software Engineer - Data Infrastructure

• Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid
• Leading key data infrastructure projects such as improving ML development golden paths, implementing offline streaming solutions for data freshness, building net new ETL pipeline infrastructure, and evolving data warehouse or data lakehouse capabilities.
• Working with stakeholders in other teams and functions to define technical roadmaps for key backend systems and abstractions across Plaid.
• Debugging, troubleshooting, and reducing operational burden for our Data Platform.
• Growing the team via mentorship and leadership, reviewing technical documents and code changes.

• 6+ years of software engineering experience
• Extensive hands-on software engineering experience, with a strong track record of delivering successful projects within the Data Infrastructure or Platform domain at similar or larger companies.
• Deep understanding of one of the below:

• Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration.

• Strong cross-functional collaboration, communication, and project management skills, with proven ability to coordinate effectively.
• Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions.
• Demonstrated leadership abilities, including experience mentoring and guiding junior engineers.
• Nice-to-Have:

• Experience with Databricks
• Experience with Airflow
• Experience with AWS EMR
• Experience with Python

1098 Harrison Street, San Francisco, CA 94103 Hybrid work $207,600 - $273,600 a year - Full-time, Pulled from the full job description

• 401(k)
• Health insurance
• Vision insurance
• Dental insurance, * Zone 1$207.6K - $273.6K * Offers Equity

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., 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. Compensation Range: $207.6K - $273.6K

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, Washington D.C., London and Amsterdam. Making data driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. Engineers on Data Infrastructure are domain experts in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies. We scale our existing data pipelines in a performant and cost efficient way while creating the necessary abstractions to make developing on top of this platform extremely simple for other engineers at Plaid.