Senior Data Engineer

Checkr-posted 3 months ago
$162,000 - $190,000/Yr
Full-time • Senior
San Francisco, CA
1,001-5,000 employees
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Checkr is building the data platform to power safe and fair decisions. Established in 2014, Checkr’s innovative technology and robust data platform help customers assess risk and ensure safety and compliance to build trusted workplaces and communities. Checkr has over 100,000 customers including DoorDash, Coinbase, Lyft, Instacart, and Airtable. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company. 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.
  • 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 and Python.
  • Expertise in understanding of 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.).
  • Knowledge of security best practices and data privacy concerns.
  • Strong problem-solving skills and attention to detail.
  • Experience/knowledge of data processing platforms such as Databricks or Snowflake.
  • An understanding of Graph and Vector data stores.
  • A collaborative and fast-moving environment.
  • Be part of an international company based in the United States.
  • Learning and development reimbursement allowance.
  • Competitive compensation and opportunity for professional and personal advancement.
  • 100% medical, dental, and vision coverage for employees and dependents.
  • Additional vacation benefits of 5 extra days and flexibility to take time off.
  • Reimbursement for work from home equipment.
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