Staff Data Engineer - Databricks

CVS Health•Work At Home-Illinois, IL

3d•$130,295 - $260,590

About The Position

CVS Health is seeking a highly experienced Staff Data Engineer for a senior individual contributor role focused on designing, building, and scaling data infrastructure. The role addresses complex data challenges, drives technical strategy, and mentors data engineers. The work supports data-driven decisions and value for customers. The engineer will lead the architecture of scalable, reliable, and fault-tolerant data pipelines and platforms, while also developing and optimizing core pipelines with SQL, Python, Apache Spark, and cloud-native services. The role partners with data scientists, analysts, and product managers to translate business needs into data solutions, and ensures operational health through monitoring, alerting, and logging. It also champions adoption of useful technologies and establishes data quality and governance practices. The position requires 7 or more years of data engineering experience, including Azure and Databricks experience, and a bachelor's degree in Computer Science or Engineering. The stated pay range is $130,295 to $260,590. This full-time role is eligible for a CVS Health bonus, commission or short-term incentive program, and an equity award target. Benefits include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, subject to eligibility.

Requirements

At least 7 years of hands-on experience in data engineering or a similar role, with a record of designing and implementing large-scale data systems.
Proficiency in Python and strong proficiency in SQL.
Extensive experience with at least one major cloud provider's data ecosystem; Azure and Databricks experience is required.
Strong knowledge of data warehousing concepts, ETL/ELT principles, and modern data lake architectures.
Proven ability to design and build scalable and resilient data systems from scratch.
Excellent communication, collaboration, and problem-solving skills, including the ability to explain complex technical concepts to varied audiences.
Bachelor's degree in Computer Science or Engineering.

Nice To Haves

Experience with Infrastructure as Code, such as Terraform, and CI/CD pipelines.
Familiarity with streaming technologies such as Kafka or Kinesis.
Familiarity with healthcare data and healthcare insurance feeds.

Responsibilities

Design and build scalable, reliable, and fault-tolerant data pipelines and platforms, and guide architecture for data ingestion, transformation, and storage.
Develop and optimize core data pipelines using SQL, Python, Apache Spark, and cloud-native services.
Mentor and coach data engineers, provide technical guidance, and promote best practices, code quality, and professional growth.
Partner with data scientists, analysts, and product managers to translate business requirements into robust, efficient data solutions.
Maintain operational health of data systems by implementing monitoring, alerting, and logging and addressing performance bottlenecks and system failures.
Track data engineering trends and lead adoption of tools and approaches that improve the platform and team capabilities.
Establish and enforce data quality standards and governance practices to ensure data integrity and reliability.