Data Engineer

About the Team

The Data Platform team is dedicated to building and delivering data assets that empower our customers with visibility into their plan costs and clinical outcomes. Reporting to the Chief Data and Analytics Officer, this team collaborates closely with Data Science, Analytics, and other departments to drive data-driven decision-making across the organization.

About the Role

As a Data Engineer, you will play a key role in designing, building, and maintaining the data infrastructure that supports our organization. You’ll work closely with cross-functional teams to identify optimal solutions for data analysis, ensuring high data quality and seamless execution. This role requires strong problem-solving abilities, multitasking skills, and the ability to collaborate effectively with diverse stakeholders.

Key Responsibilities

• Data Pipelines: Design, develop, and maintain efficient data pipelines using Spark (PySpark, Spark SQL).
• Data Modeling: Collaborate with analytics consumers to design logical and physical schemas, improve existing data models, and create new ones.
• Cross-Functional Collaboration: Partner with teams across Product, Engineering, Data Science, Analytics/BI, and Operations to understand data needs and deliver tailored solutions.
• Data Expertise: Build deep expertise in data domains, including healthcare claims and member experience, and ensure high data quality.
• Next-Generation Data Ecosystem: Leverage industry best practices to build scalable, cutting-edge systems for data collection, movement, storage, and analysis.
• Agile Development: Work within an agile framework to drive iterative and efficient development processes.

Qualifications

• Education: Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
• Experience:
• 2+ years of experience as a Data Engineer, with proficiency in a programming language such as Python (PySpark) or Scala, and strong SQL skills.
• 2+ years of experience in schema design, dimensional data modeling, and large-scale data warehousing architecture.
• Proven expertise in designing, implementing, and maintaining efficient ETL pipelines.
• Technical Skills:
• Hands-on experience with distributed data systems such as Spark, Presto, Hive, and Redshift.
• Familiarity with workflow management tools or schedulers is a plus.
• Experience in Looker administration, including managing permissions, maintaining LookML models, and optimizing dashboards, is a bonus.
• Soft Skills: Excellent communication and collaboration skills to work effectively with stakeholders across Engineering, Product, Data Science, Analytics/BI, and Operations.

Pay Transparency Statement

This is a hybrid position based out of one of our offices: San Francisco, CA, Plano, TX, or Lehi, UT. Hybrid employees are expected to be in the office three days per week (Plano, TX) or two days per week (San Francisco, CA and Lehi, UT). #LI-hybrid

The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/benefits/.