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Mid-level generalist Data Engineer in metro with broad Azure/Databricks requirements increases competition.
Core data engineering skills are transferable, but Azure/Databricks and governance needs create moderate domain specificity.
Explicit 4–6 years plus mandatory Azure, Databricks, ADF, and governance skills increases shortlisting strictness.
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Design and implement scalable data pipelines and analytics solutions using Azure services, ensuring optimal performance and data quality.
Develop and maintain data models, ETL processes, data governance, and security frameworks across Databricks and enterprise data warehouse ecosystems.
Collaborate with data scientists, analysts, and business stakeholders to fulfill data requirements, create dashboards, and support business decision-making.
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
4-6 years of experience in data engineering.
Hands-on experience with Azure services including Azure Data Factory, Azure Databricks, Azure Data Lake Storage, and Microsoft SQL Server.
Experience developing and maintaining data governance and security frameworks in Databricks and EDW ecosystems.
Experienced with cloud data platforms and Azure ecosystem tools, including orchestration and big data storage.
Proficient in SQL, ETL development, data warehousing, and working within version-controlled development workflows.
Skilled in collaborating across teams including co-development with data scientists and analysts to deliver data-driven business insights.