The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
The ad says“Experience with AWS EMR”
The ad says“Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions”
The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
The ad says“Experience with Databricks”
The ad says“Experience with Python”
The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
The ad says“Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions”
The ad says“Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions”
The ad says“Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration”
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
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
Benefits
Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft
Preferred experience
Data Infrastructure systems, including Data Warehouses, Data Lakehouses, Apache Spark, Streaming Infrastructure, Workflow Orchestration
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
Proficiency in coding, testing, and system design, ensuring reliable and scalable solutions
Demonstrated leadership abilities, including experience mentoring and guiding junior engineers
Strong cross-functional collaboration, communication, and project management skills, with proven ability to coordinate effectively
Deep understanding of one of the below:
6+ years of software engineering experience
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!
