Staff Data Engineer

About the role

This Staff Data Engineer position focuses on developing and maintaining Checkr's centralized data platform. The platform is crucial for powering customer-facing products that support fair and safe hiring decisions. The role involves working on high-impact projects that contribute to the company's next-generation product offerings.

Key responsibilities include architecting and building end-to-end data platforms that are performant, reliable, and scalable. The engineer will also be responsible for creating and maintaining data pipelines, foundational datasets, and designing database architectures. A significant part of the role involves developing audits to ensure data quality and building scalable dashboards and reports.

Success in this role means delivering robust data solutions that meet the demands of a fast-paced environment. It also involves effectively mentoring junior engineers and collaborating with internal stakeholders to understand requirements and resolve production issues. The ideal candidate will have a strong background in large-scale data processing and a commitment to data privacy and security.

The compensation for this role ranges from $140,000 to $200,000 USD annually.

Skills that matter here

• PySpark: This role requires proficiency in PySpark for developing and delivering scalable data platforms and processing large-scale data.
• Python: Python proficiency is essential for building and maintaining data pipelines and other data platform components.
• SQL: SQL expertise is needed for data modeling, database architecture design, and managing relational databases.
• AWS: Experience with the AWS stack is required for leveraging cloud services to build and manage big data technologies.
• Datalake: The role involves working with Datalake technologies to architect and build scalable data platforms.
• Kafka: Knowledge of Kafka will be applied in designing and implementing real-time data processing components within the data platform.

Who this role suits

• A person with over a decade of experience designing and delivering large-scale data platforms.
• Someone who enjoys guiding and mentoring less experienced engineers.
• An individual who can effectively collaborate with both internal and external stakeholders.
• A problem-solver adept at investigating and resolving production data issues.

From the employer

• Architect, design, lead and build end-to-end performant, reliable, scalable data platform.
• Mentor, guide and work with junior engineers.
• Collaborate with customers and internal stakeholders.
• Monitor, investigate, and resolve production issues.
• Create and maintain data pipelines and foundational datasets.
• Design and build database architectures.
• Develop audits for data quality.
• Create scalable dashboards and reports.

• 10+ years of experience in designing and delivering scalable data platforms.
• Experience with large-scale data processing pipelines.
• Proficiency in PySpark, Python, and SQL.
• Expertise in data modeling and relational databases.
• Experience with big data technologies and AWS stack.
• Knowledge of security best practices and data privacy concerns.
• Strong problem-solving skills.

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