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CheckrCheckr

Staff Data Engineer

Staff Data Engineer building and evolving Checkr's centralized people data platform and foundational datasets that power all AI verification products. Requires 10+ years experience with large-scale data pipelines, PySpark, Spark, Kafka, Iceberg, and AWS services; will mentor juniors and own architecture.

About the job

What you'll do

  • Architect, design, lead, and build an end-to-end, performant, reliable, scalable data platform.
  • Work as an independent contributor: solve problems and deliver high-quality solutions with minimal oversight and strong ownership.
  • 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: you 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.

What you bring

  • 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.
  • Nice to have: Experience or knowledge of data processing platforms such as Databricks or Snowflake.
  • An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.

What We Offer

  • 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

Skills

Pyspark, Python, SQL, ETL, ELT, Kafka, Spark, Iceberg, AWS, EKS, Emr, Glue, Athena, S3, MongoDB

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