Senior Data Engineer

As a technical contributor on the People Data team, you'll help build and scale Checkr's centralized people data platform, the system that stores and serves the identity and people records powering every Checkr product.

As a Senior Data Engineer, you'll lead the execution of core services and data pipelines, delivering reliable, high-quality solutions that keep the platform fast and accurate as our product surface grows. You'll partner closely with engineering, product, and data teams across Workforce, Tenant, Trust, and Personal, directly enabling the fair and safe hiring decisions at the heart of Checkr's growth.

What you'll do

• Design, build, and ship new capabilities and data pipelines for the People Data platform, from design through release
• Lead the execution of core services with strong ownership, balancing speed to market with long-term scalability and reliability
• Build and maintain large-scale data processing pipelines (batch and streaming) that serve identity and people records across Checkr's products
• Partner with Product and cross-functional teams to scope appropriately sized initiatives and shape a roadmap that meets business needs quarter over quarter
• Ensure platform availability and data accuracy by participating in on-call rotation, resolving production issues, and driving preventative improvements
• Mentor engineers on the team and contribute to the broader engineering organization through technical reviews, showcases, and proposals

What you bring

• 5+ years of software engineering experience building scalable, performant data platforms or backend services
• Strong proficiency in Python, PySpark, and SQL, with solid Computer Science fundamentals across data structures, algorithms, and relational/NoSQL databases (e.g., MongoDB)
• Experience building large-scale data processing pipelines using ETL/ELT, batch, and stream processing
• Familiarity with big data technologies such as Kafka, Spark, Iceberg, and data lakes, and the AWS stack (EKS, EMR, Glue, Athena, S3)
• Experience with data modeling, domain modeling, and system architecture, with a proven track record of writing clear, tested code
• Knowledge of security best practices and data privacy concerns, and a strong sense of ownership across the full development lifecycle
• Nice to have: experience with data processing platforms such as Databricks or Snowflake

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