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Metro location and popular data-engineer title but senior Azure/Databricks specialization narrows applicant pool.
Strong Azure Databricks and Lakehouse requirements moderately limit cross-industry transferability.
Explicit 8+ years plus mandatory Azure Databricks, Python/PySpark, and SQL create strict screening filters.
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Design and develop scalable data pipelines using Python/PySpark within Azure environment.
Architect and implement Azure ETL/ELT solutions leveraging Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, and Lakebase.
Lead technical guidance, code reviews, and mentorship of junior engineers while troubleshooting pipeline and performance issues.
8+ years of experience in Data Engineering/Data Warehousing.
5+ years of experience with Python/PySpark.
8+ years of experience with SQL including complex queries and stored procedures.
Strong experience with Azure Databricks, Data Factory, Blob Storage, Synapse, Azure SQL, Lakebase, and Unity Catalog.
Proven ability to lead and mentor technical teams in Azure data engineering projects.
Experienced in translating complex business requirements into scalable data solutions using Azure services.
Familiarity with best engineering practices, code reviews, and project delivery tools like Git, Azure DevOps, and Jira.