Staff Data Engineer

About the role

The Staff Data Engineer on the People Data team helps build and evolve the centralized platform that powers every Checkr product. This platform stores and serves the identity and people records that underpin Checkr's Workforce, Mortgage, Tenant, Trust, and Personal products.

Responsibilities

• Architect, design, lead, and build an end-to-end, performant, reliable, scalable data platform.
• Solve complex distributed systems and data engineering challenges while influencing the technical direction of one of the company's most critical platforms.
• Mentor and guide junior engineers to deliver complex, next-generation features.
• Bring a customer-centric, product-oriented mindset. Collaborate with customers and internal stakeholders to resolve product ambiguities and ship features that solve real customer problems.
• Partner with engineering, product, design, and other stakeholders to design and architect new features.
• Experimentation mindset: autonomy and empowerment to validate a customer need, get team buy-in, and ship a rapid MVP.
• Quality mindset: treat quality as a non-negotiable part of your software deliverables.
• Analytical mindset: instrument and deploy new product experiments with a data-driven approach.
• Monitor, triage, and resolve production issues for the team's services.
• Create and maintain data pipelines and foundational datasets to support product and business needs.

Requirements

• 10+ years designing, implementing, and delivering highly scalable, performant data platforms.
• Experience building large-scale data processing pipelines using ETL/ELT, batch, and stream processing.
• Expert-level proficiency in PySpark, Python, and SQL.
• Expertise in data modeling, relational databases, and NoSQL data stores (e.g., MongoDB).
• Experience with big data technologies such as Kafka, Spark, Iceberg, data lakes, and the 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.

Qualifications

• Experience or knowledge of data processing platforms such as Databricks or Snowflake is a plus.

Skills

• Expert-level proficiency in PySpark, Python, and SQL.
• Expertise in data modeling, relational databases, and NoSQL data stores (e.g., MongoDB).
• Experience with big data technologies such as Kafka, Spark, Iceberg, data lakes, and the 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.

Benefits

• A fast-paced and collaborative environment
• Learning and development allowance
• Competitive cash and equity compensation, and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Flexible PTO policy
• Monthly wellness stipend

Pay

• On-target Earnings OR Base Salary range (San Francisco, CA): $196,000 - $230,000 USD
• On-target Earnings OR Base Salary range (Denver, CO): $166,000 - $195,000 USD

Schedule

• Individuals are expected to work from the office 3+ days a week.