Responsibilities

Own end-to-end data systems and pipelines that other teams and customers rely on
Design and implement data integrations across multiple backend business systems, ensuring efficient and reliable data flows
Work on streaming data processing using frameworks like Apache Beam to handle real-time data ingestion and transformation
Build and maintain APIs to enable seamless data access and sharing across internal teams and platforms
Manage orchestration and automation of workflows using Airflow on Kubernetes
Define what "correct" means for the data you own, and back it with monitoring, alerting, and integration tests
Build reusable patterns and components (hooks, plugins, alerting utilities) that are easily adoptable by other engineers and processes
Break down ambiguous work into actionable tasks, surface edge cases and failure modes early, and clarify requirements with stakeholders
Communicate tradeoffs, assumptions, and risks clearly in design reviews and PRs
Drive design decisions and shape how the team builds going forward

Requirements

5+ years of Data Engineering experience
3+ years of Airflow experience
Expert in Python and SQL
Strong working knowledge of Snowflake, Airflow, DBT, GCP
BS in Computer Science or related field
Must be currently authorized to work in the USA without sponsorship or transfer
Previous work experience in Fintech, Payments, or related industries (nice to have)
Experience with managing Airflow on Kubernetes (nice to have)
Experience with data streaming (Apache Beam, Dataflow) (nice to have)
Experience with automated ETL (Fivetran, HighTouch) (nice to have)

Benefits

Senior Data Engineer

Job Description