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Strong brand, generalist Data Engineer title, and mid-level experience increase applicant competition.
Core data engineering skills are transferable, though healthcare domain knowledge gives moderate bias.
Explicit 5+ years plus mandatory Databricks/Snowflake/ETL/DevOps skills create strict shortlisting filters.
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Design, build, and operate scalable ETL/ELT pipelines using Databricks, Snowflake, and Azure cloud technologies.
Develop cloud-native data platforms and enable analytics, reporting, and AI/ML workloads with trusted, high-quality data assets.
Optimize data workflows for performance, reliability, and cost efficiency while ensuring compliance with enterprise data governance and security standards.
Bachelor's degree in Computer Science or Engineering related field.
5+ years of experience as a Data Engineer or in data platform/analytics engineering roles.
3+ years hands-on experience with Databricks and/or Snowflake, SQL, data modeling, and data transformations.
3+ years experience building ETL/ELT pipelines and familiarity with source control and DevOps (Azure DevOps, GitHub, CI/CD).
Experienced in designing and deploying enterprise-scale, cloud-native data platforms with emphasis on operational efficiency and governance.
Skilled in troubleshooting, performance tuning, and production issue resolution for large-scale data processing pipelines.
Able to contribute to architectural discussions and mentor junior engineers, with knowledge of AI-powered solution development and responsible AI practices.