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, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data architecture and datasets, while maintaining correctness and completeness of underlying data. We provide golden datasets and tooling to teams across engineering, product, and business to help them explore our data quickly and get the 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 systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, and proactive across the company.
Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analytics, ML 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 help build the right datasets and drive and define data standards and data culture within the team.
- You will collaborate with and have strong cross-functional partnerships with literally all teams at Plaid such as Engineering, Product, ML, Data Science, Data Analytics, Marketing, and Finance.
- You will be responsible for providing good technical guidance for the team and collaborating with team members on brainstorming ideas and building suitable data products.
Responsibilities
- Understanding different aspects of the Plaid product and strategy to inform golden dataset choices, design and data usage principles.
- Have data quality and performance top of mind while designing datasets.
- Leading key data engineering projects that drive collaboration across the company.
- Advocating for adopting industry tools, standards and best practices at the right time.
- Build and maintain end to end data pipelines that power our data lake and data warehouse.
- Improve data usability through well-documented datasets built on predefined data quality, uptime, and usefulness SLAs.
Qualifications
- 2+ years of dedicated data engineering experience, solving complex data pipeline issues at scale.
- You have experience building data models and data pipelines on top of large datasets (in the order of terabytes to petabytes).
- You value SQL as a flexible and extensible tool and are comfortable with modern SQL data orchestration tools like DBT, Mode, and Airflow.
- You have experience working with data warehouses and data lakes such as Redshift, Snowflake, Databricks.
- You have experience building and maintaining batch, real-time pipelines using technologies such as Spark, Flink, Kafka.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of…