At Plaid, we believe that the way consumers and businesses interact with their finances will drastically improve in the next few years. Our goal is to build the tools and infrastructure for developers to create this next generation of financial services applications. Today, hundreds of companies such as Venmo, Square, and Coinbase rely on Plaid to integrate with banks and the financial system.
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.
In addition, Plaid will not be successful if we can't move quickly. We build the data and machine learning infrastructure to enable Plaid engineers to prototype and iterate on products and features built on top of consumer-permissioned financial data.
We work in Python, Golang, and Typescript. Our systems are built on top of Docker, Kubenetes, Mesos, Spark, S3, Redshift, Airflow, and ElasticSearch.
As an engineer, you’ll help build, scale, and design the next generation of Plaid’s product infrastructure. 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.
What excites you
Defining the long-term technical roadmap for machine learning and data-driven iteration at Plaid
Leading key data infrastructure projects across multiple work streams, such as building an internal ML-as-a-service platform and an incremental stream processing pipeline
Working with stakeholders in other teams and functions to define technical roadmaps for key backend systems and abstractions across Plaid
Mentoring other engineers into senior roles and establishing a culture of technical excellence
What excites us
Deep industry experience laying the technical foundations for top-tier teams
Production experience building out data systems that make it a breeze to ingest, process, and analyze terabytes of data
Empathy and enthusiasm for understanding other teams’ challenges and the ability to influence them towards the right technical path for the org
Knowledge of Spark, Hadoop, Airflow, or other data infrastructure tools
A good understanding of core ML principles and a solid understanding of statistics and CS theory
A record of mentoring experienced engineers around you and helping them grow
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.