Senior Data Engineer

Role overview

Responsibilities

• Use understanding of Plaid products and strategy to guide dataset selection, design, and data-use principles.
• Design for data quality and performance; lead collaborative data engineering projects.
• Own SQL and Python pipelines powering the data lake and warehouse.
• Document datasets and define quality, uptime, and usefulness.
• Build internal datasets and visualizations and establish service-level agreements for the area.
• Promote timely adoption of industry tools and practices.

Qualifications

• At least four years of dedicated data engineering experience solving complex pipeline issues at scale.
• Experience building data models and pipelines over datasets of approximately 500 TB to petabytes.
• Strong SQL skills and experience with orchestration tools such as dbt, Mode, or Airflow.
• Experience with data warehouses and lakes such as Redshift, Snowflake, or Databricks.
• Experience with batch and real-time pipelines using technologies such as Spark or Kafka.
• Knowledge of schema design and evolving analytics schemas over unstructured data.
• Ability to develop proofs of concept, manage and improve infrastructure, work collaboratively with stakeholders, and protect data privacy and integrity.

About Plaid

Compensation

• Additional compensation may include equity and/or commission, depending on the position offered.
• Pay is based on factors including role scope, responsibilities, work experience, skills, and location; the posting provides no salary cadence.