Senior Data Engineer, Checkr

• 6-7+ years of development experience in the field of data engineering (5+ years writing PySpark)
• Experience building large-scale (100s of Terabytes and Petabytes) data processing pipelines - batch and stream
• Experience with ETL/ELT, stream and batch processing of data at scale
• Strong proficiency in PySpark, Python, and SQL
• Expertise in understanding database systems, data modeling, relational databases, NoSQL (such as MongoDB)
• Experience with big data technologies such as Kafka, Spark, Iceberg, Datalake, and AWS stack (EKS, EMR, Serverless, Glue, Athena, S3, etc.)
• An understanding of Graph and Vector data stores (preferred)
• Knowledge of security best practices and data privacy concerns
• Strong problem-solving skills and attention to detail

Desirable

• We're seeking an experienced Senior Data Engineer to join our Data Operations team. This team plays a crucial role in our mission by developing and maintaining the systems that conduct accurate and efficient background checks
• As a Senior Data Engineer on the Data Operations team, you'll work on high-impact projects that directly contribute to the core functionality of Checkr's background check services.
• You'll be instrumental in improving our data ingestion and processing capabilities and ensuring the reliability and accuracy of our core product
• Create and maintain data pipelines and foundational datasets to support product/business needs
• Design and build database architectures with massive and complex data, balancing with computational load and cost
• Develop audits for data quality at scale, implementing alerting as necessary
• Create scalable dashboards and reports to support business objectives and enable data-driven decision-making
• Troubleshoot and resolve complex issues in production environments
• Work closely with product managers and other stakeholders to define and implement new features