About the Role
We are seeking a strong Senior Data Engineer to build and maintain scalable, high-quality data pipelines powering Checkr’s centralized data platform. As a Senior Engineer, you will independently deliver complex features, contribute to system design, and collaborate with cross-functional partners to support the next generation of our data products.
What You’ll Do
- Independently design and implement complex batch and streaming pipelines using PySpark, SQL, and AWS services.
- Navigate ambiguity with guidance, translating high-level direction into well-scoped, high-quality technical solutions.
- Work cross-functionally with product, design, analysts, and engineers to ship impactful features and improve data workflows.
- Contribute to architectural discussions and system improvements without owning long-term strategy.
- Ensure pipeline reliability and data quality, implementing testing, monitoring, and observability best practices.
- Investigate and resolve production issues for services owned by the team.
- Write performant, maintainable code that aligns with engineering standards.
- Support the team in building foundational datasets that enable analytics, ML, and customer-facing features.
What You Bring
- 6–7+ years of experience in data engineering with strong hands-on execution ability.
- Proficiency with PySpark, Python, and SQL, including debugging and performance optimization.
- Experience building large-scale pipelines (up to terabytes or larger), with exposure to streaming systems such as Kafka.
- Strong knowledge of data modeling, relational databases, and NoSQL stores.
- Experience with AWS services such as EMR, Glue, Athena, Lambda, and S3.
- Exposure to Iceberg or other lakehouse technologies (nice to have).
- Understanding of security and data privacy fundamentals.
- Strong problem-solving skills, attention to detail, and ability to execute independently.
- Knowledge of Databricks, Snowflake, or Graph/Vector stores is a plus.
