Data Engineer - Cloud ETL, Azure, Data Bricks, Snowflake, Pyspark
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand plus popular mid-level data engineer profile with broad cloud ETL skills attracts strong competition.
Healthcare data governance and domain knowledge preference reduces cross-industry transferability to a moderate degree.
Explicit 5+ years plus mandatory Databricks, Snowflake, Python, Airflow, and SQL increases filter strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain ETL/ELT pipelines using Databricks, Snowflake, Python, and Teradata supporting enterprise reporting, analytics, and AI/ML.
Develop and support workflow orchestration via Airflow, implement CI/CD using GitHub/GitHub Copilot, and ensure operational monitoring and production support.
Collaborate with business and technical teams to gather requirements and deliver compliant data solutions within healthcare regulations and data governance frameworks.
Minimum Requirements
Bachelor's degree in Computer Science, Information Systems, or related field.
5+ years of experience in Data Engineering, Data Warehousing, or ETL development.
Hands-on experience with Databricks, Snowflake, Teradata, Python, UNIX, Airflow, and GitHub/GitHub Copilot.
Strong SQL and data modeling skills, knowledge of AI/ML data engineering support, and compliance with healthcare data governance.
Ideal Candidate Profile
Experienced with enterprise-scale data engineering supporting AI/ML workloads in regulated environments, preferably healthcare domain.
Operationally responsible for end-to-end ETL pipelines and production deployments, showing capability in troubleshooting and performance tuning.
Collaborates cross-functionally between technical and business teams, with emphasis on data quality, compliance, and scalable data solutions.