Staff Data Platform Engineer - Scale & Impact

Checkr - Chile; San Francisco (CA); Hybrid; USD 224,000 - 264,000; Full time

Benefits offered by this job

Fast-paced environment

Learning & development allowance

Competitive cash and equity, and scope

100% medical, dental, and vision

Fertility, adoption, parental planning

Flexible PTO

Monthly wellness stipend

Job summary

Checkr is seeking a Staff Data Engineer on the People Data team to build and evolve a centralized platform powering Checkr’s Workforce, Mortgage, Tenant, Trust, and Personal products. You’ll own core services, data pipelines, and architecture to ensure a scalable, reliable platform for AI-powered verification across high-stakes decisions.

You will solve complex distributed data engineering challenges, mentor engineers, and collaborate with stakeholders to deliver features with a customer-centric

Qualifications

• 10+ years designing, implementing, and delivering highly scalable 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.
• 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.

Responsibilities

• 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.

Skills

Data platform design

ETL/ELT pipelines

PySpark

Python

SQL

Data modeling

NoSQL (MongoDB)

Kafka

Spark

Iceberg

AWS stack (EKS/EMR/Glue/S3)

Security best practices

Databricks or Snowflake (nice to have)

Tools

Databricks

Snowflake

Kafka

Spark

Job description

Checkr is seeking a Staff Data Engineer on the People Data team to build and evolve a centralized platform powering Checkr’s Workforce, Mortgage, Tenant, Trust, and Personal products. You’ll own core services, data pipelines, and architecture to ensure a scalable, reliable platform for AI-powered verification across high-stakes decisions.

You will solve complex distributed data engineering challenges, mentor engineers, and collaborate with stakeholders to deliver features with a customer-centric