Data Engineer II

Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent experience.
2+ years of experience building scalable, high-performance, cloud-based data lake or warehouse solutions.
Strong experience with SQL and programming languages, especially Python and Scala.
Familiarity with version control tools (e.g., GitHub) and CI/CD processes.
Solid understanding of distributed computing frameworks such as Apache Spark or Hadoop.
Hands-on experience building pipelines in Databricks, including use of its APIs.
Proficient with AWS cloud infrastructure and security best practices.
Working knowledge of Infrastructure as Code tools like Terraform.
Understands healthcare data standards such as CPT, HCPCS, ICD-10, DRG, MS-DRG, APR-DRG, etc.
Strong problem-solving skills with the ability to take initiative and lead ambiguous projects to completion.
Thrives in a fast-paced environment with excellent organizational and prioritization skills.
Passion for building infrastructure and processes from the ground up, rather than relying on what’s already in place.
Willingness to collaborate cross-functionally and support other teams when needed.

Design, build, and maintain robust data pipelines to ingest and transform data from diverse source systems.
Use programming languages like Python, Scala, and SQL to create scalable, maintainable, and efficient solutions—including batch pipelines and serverless functions.
Develop APIs and data microservices to enable secure data sharing within and outside the organization, and build integrations with public datasets to enrich analytics.
Implement data quality checks and monitoring to ensure accuracy, consistency, and reliability of the data.
Collaborate with data scientists, analysts, and product managers to understand data needs and deliver appropriate solutions.
Apply agile principles to drive automation, iteration, and collaboration across teams.

No preferred qualifications provided.