Experienced Data Engineer - Data Engineering - Plaid

Job Title: Experienced Data Engineer - Data Engineering
Job Location: San Francisco
Job Listing URL: https://jobs.lever.co/plaid/022278b3-0943-44b3-a54b-1de421017589
Job Description: 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. #LI-Hybrid

The main goal of the DE team in 2024-25 is to build robust golden data sets to power our business goals of creating more insights based products. 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. Data Engineers heavily leverage SQL and Python to build data workflows. We use tools like DBT, Airflow, Redshift, ElasticSearch, Atlanta, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. Our engineering culture is IC-driven -- we favor bottom-up ideation and empowerment of our incredibly talented team. We are looking for engineers who are motivated by creating impact for our consumers and customers, growing together as a team, shipping the MVP, and leaving things better than we found them.

You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownership and scope of internal datasets and visualizations across Plaid which is a currently unowned area that we intend to take over and build SLAs on. You will have the opportunity to learn best practices and up-level your technical skills from our strong DE team and from the broader Data Platform team. You will collaborate with and have strong and cross functional partnerships with literally all teams at Plaid from Engineering to Product to Marketing/Finance etc.
Responsibilities
Defining the long-term technical roadmap for building a data-driven culture at Plaid.
Deeply understanding different aspects of the Plaid product and strategy to inform golden dataset choices, design and data usage principles.
Focus on data quality and privacy.
Leading key data engineering projects that drive collaboration across the company.
Mentoring engineers, operations, and data analysts on best practices for data organization and query performance.
Advocating for adopting industry tools and practices at the right time.
Owning core SQL and Python data pipelines that power our data lake and data warehouse.
Well-documented data with defined dataset quality, uptime, and usefulness.
Qualifications
6+ years of dedicated data engineering experience, solving complex data pipelines issues at scale.
You value SQL as a flexible and extensible tool, and are comfortable with modern SQL data orchestration tools like DBT, Mode, high touch, and Airflow.
Experience working both real-time systems like Kinesis, Kafka, Flink, and batch data pipelines in Redshift, Presto, and Data Lakes.
You appreciate the importance of schema design, and can evolve an analytics schema on top of unstructured data.
You are excited to try out new technologies. You like to produce proof-of-concepts that balance technical advancement and user experience and adoption.
You like to get deep in the weeds to manage, deploy, and improve low level data infrastructure.
You are empathetic working with stakeholders. You listen to them, ask the right questions, and collaboratively come up with the best solutions for their needs.
You are a champion for data privacy and integrity, and always act in the best interest of consumers.