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Generalist mid-level Data Engineer with broad Azure skillset and metro hiring context drives high competition.
Core data engineering skills are transferable across industries though healthcare domain knowledge moderately increases fit sensitivity.
Explicit 2–5 years plus specific Azure Databricks/ADF/Snowflake, ADLS, Power BI and DevOps requirements make screening stringent.
Design, build, and maintain scalable data pipelines and ETL processes for the analytics data platform/lakehouse.
Develop and implement data visualizations and reports using PowerBI.
Implement, monitor, and optimize security measures and performance of data pipelines and storage solutions.
2-5 years of hands-on experience as a Data Engineer, preferably with Microsoft Azure cloud platform.
Proficiency with Azure data stack including Azure Databricks or Snowflake, ADLS Gen2 Lakehouse, Azure Data Factory, SQL Server, and Power BI.
Strong programming skills in Python, SQL, or Scala.
Bachelor's or Master's degree in Computer Science or related field.
Experienced in working with Microsoft Azure cloud data platforms and tools, emphasizing scalable and secure data engineering infrastructure.
Able to collaborate closely with product owners, data scientists, and analysts to translate requirements into technical solutions.
Skilled in developing data visualizations and reports to drive data storytelling and decision-making.