Back
Mid-level, popular data-engineer title, metro hiring and broad Azure/Databricks requirements increase applicant competition.
Core data engineering skills are broadly transferable; healthcare experience is only desirable.
Explicit 4–6 years plus mandatory Databricks, advanced SQL, Data Vault and Azure skills make screening strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and develop cloud-based data platforms using commercial tools and proprietary CACI software focusing on healthcare analytics.
Lead and apply best practice design principles for data solutions in cloud environments.
Collaborate within a multi-skilled team to develop products targeting the healthcare market's long-term needs.
4-6 years of experience in data warehousing or data platform development.
Experience working in an agile, structured product development environment.
Core technical skills in database design for analytics (Data Vault & Kimball), advanced SQL, Databricks, Python, and ETL pipeline development from disparate sources.
Not explicitly mentioned in the JD: mandatory education background, explicit notice period, or strict location constraints.
Experienced data engineer with a background in cloud-based data platform development, preferably within healthcare or related analytics products.
Strong knowledge of Azure ecosystem including Entra-ID, Key Vault, Data Lake and familiarity with DevOps, CI/CD pipelines, and metadata-driven design.
Comfortable working in a collaborative, agile product development environment and able to communicate effectively across teams.