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Niche Azure/Databricks/PySpark requirements and secure environment reduce applicant density despite metro location.
Core data engineering skills are transferable, though financial services controls and secure Azure specifics add domain bias.
Specific mandatory Azure, Databricks, PySpark and secure-Azure experience make shortlisting moderately strict.
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Build and operationalize data solutions using Azure services including Data Factory, Data Flows, Databricks, Data Lake Gen 2, and Azure SQL.
Migrate on-premise data warehouses to Azure cloud data platforms.
Maintain and enhance controls to reduce operational risk and improve customer outcomes.
Experience with Azure data engineering tools: Data Factory, Databricks, Data Lake Gen 2, Azure KeyVault, Service Principals, Managed Identities.
Proficient in Py-Spark and skilled in relational and dimensional data modeling including big data technologies.
Experience in capacity planning and performance tuning for ADF and Databricks pipelines.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in working with offshore development teams and collaborating across project lifecycles including requirement analysis, testing, and release.
Skilled in stakeholder management, process adherence, planning, and documentation.
Ability to interact effectively with business stakeholders for requirement gathering and query resolution.