Responsibilities
- 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
Requirements
- 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
