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Databricks Data Engineer; Healthcare

Job in Idaho Falls, Bonneville County, Idaho, 83401, USA
Listing for: Fides Info Sys, Inc
Full Time position
Listed on 2026-02-27
Job specializations:
  • Engineering
    Data Engineer
  • IT/Tech
    Data Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Databricks Data Engineer (Healthcare)

FIDESis looking for a Data Engineer with prior Databricks experience.

The Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and infrastructure. The successful candidate will have a solid foundation in data engineering principles, substantial experience with Databricks, and a proven track record of implementing robust data solutions. Responsibilities for this role include:

  • Collaborate with cross-functional teams to understand data requirements and design appropriate solutions using Databricks.
  • Develop and maintain efficient ETL pipelines to ingest, process, and transform large volumes of data.
  • Implement data quality checks and monitoring processes to ensure data integrity and reliability.
  • Optimize and tune Databricks clusters for performance and scalability.
  • Work closely with data scientists and analysts to support their data needs and enable advanced analytics.
Requirements
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 3-5 years of experience in data engineering and big data technologies.
  • Proficiency with Databricks, Python, and SQL.
  • Strong knowledge of data warehousing concepts and best practices.
  • Hands‑on experience deploying and maintaining data pipelines using Databricks or similar tools.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Preferred Qualifications
  • Certification in Databricks and other relevant certifications.
  • Experience working with Healthcare organizations.
  • Experience with other big data technologies such as Apache Spark, Hadoop, or Kafka.
  • Knowledge of containerization technologies such as Docker and Kubernetes.
  • Experience with version control systems such as Git.
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