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Senior Data Engineer

Denver, Colorado, United StatesRemoteFull TimeSenior$185,000–$218,000 /yrPosted 2 months agoVisa sponsorship available

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Role summary

Checkr is seeking a Senior Data Engineer to build and maintain its centralized data platform. This role involves independently designing and implementing complex batch and streaming data pipelines using PySpark, SQL, and AWS services. The engineer will collaborate with cross-functional teams, contribute to system design, ensure pipeline reliability and data quality through testing and monitoring, and resolve production issues. Key technical skills include proficiency in PySpark, Python, SQL, large-scale pipeline development, streaming systems like Kafka, data modeling, relational and NoSQL databases, and AWS services. Experience with lakehouse technologies like Iceberg, Databricks, or Snowflake is a plus. The role requires 6-7+ years of experience and operates in a hybrid work model.

About CheckrCheckr is building the data platform to power safe and fair decisions. 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 Amazon, DoorDash, Netflix, Kimpton, and Anthropic.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.

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.

    • Pay Transparency Disclosure

    One of Checkr’s core values is Transparency. To live by that value, we’ve made the decision to disclose salary ranges in all of our job postings. We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.

    On-target Earnings OR Base Salary range (San Francisco, CA)
    $185,000—$218,000 USD
    On-target Earnings OR Base Salary range (Denver, CO)
    $157,000—$185,000 USD

    At Checkr, we believe an in office work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO; San Francisco, CA; Nashville, TN; and Santiago, Chile. Individuals are expected to work from the office 3+ days a week. In-office perks are provided, such as lunch five times a week, a commuter stipend, and an abundance of snacks and beverages. A relocation stipend may be available for those willing to relocate to a Checkr hub location.

    Equal Employment Opportunities at CheckrCheckr is committed to building the best product and company, which requires hiring talented and qualified individuals with a diverse set of perspectives and lived experiences. Checkr believes in hiring people of all backgrounds, including those whose histories are impacted by the justice system in accordance with local, state, and/or federal laws, including the San Francisco’s Fair Chance Ordinance.

    Applicant Privacy PolicyIf you are a California resident or are located in Alberta or British Columbia, our Applicant Privacy Policy applies to our collection and processing of your personal information when you apply for a role with us or otherwise participate in our recruitment process.

    *Legitimate Checkr emails will always include our official domain name after the @ symbol (e.g., name@checkr.com or name@ext.checkr.com).

    Sample Checkr interview questions

    • 1

      Continuous Subarrays Sum Equals K Find the total number of continuous subarrays whose sum equals K. Input: nums = [1,2,3], k = 3 Output: 2 Explanation: Both the contiguous subarray [1,2] and the single-element subarray [3] sum perfectly to the target of 3.

      codingmedium
    • 2

      Dot Product of Two Sparse Vectors Calculate the dot product of two sparse vectors. Input: nums1 = [0,1,0,0,2], nums2 = [0,0,0,0,5] Output: 10 Explanation: Multiplies the aligned non-zero values (2 * 5) and ignores all the zeros, yielding a dot product of 10.

      codingmedium
    • 3

      Alien Dictionary Order Derive the alien dictionary order from a sorted list of alien words. Input: words = ["z","x","z"] Output: "" (Empty String) Explanation: The letter 'z' cannot come before 'x' and then suddenly after 'x', creating a cycle and making the dictionary invalid.

      codingmedium
    • 4

      Palindrome After Deleting One Character Determine if a string can be a palindrome after deleting at most one character. Input: s = "abc" Output: FALSE Explanation: Deleting any single character leaves either "ab", "bc", or "ac", none of which result in a valid palindrome.

      codingmedium
    • 5

      Split Array into Consecutive Subsequences Split an array into consecutive subsequences. Input: nums = [1,2,3,4,4,5] Output: FALSE Explanation: The numbers can form [1,2,3,4], but the remaining leftover group [4,5] is too short to form a valid sequence of length 3.

      codingmedium

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