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Tier-1 employer and metro location increase applicant density, but senior niche role reduces it.
Strong Azure data engineering skills transfer across industries, finance domain knowledge moderately preferred.
Explicit 12+ years and mandatory Azure/ETL stack create strict technical filters.
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Support and maintain various DataStage and related Azure cloud data applications including Azure Data Factory, Databricks, Data Lake Gen2, and Cosmos DB.
Collaborate with development teams, business support, and end users to deliver and implement end-to-end data pipeline and ETL solutions, ensuring incident resolution within SLA.
Mentor team members, optimize technical problem-solving approaches, create/modify scripts, maintain disaster recovery plans, and participate in DR testing.
12+ years of experience with Azure Cloud Services including ADF, Databricks, Data Lake Gen2, Azure Key Vault, Cosmos DB, Azure Storage.
Skills in Python, PySpark, SQL/PL-SQL, Data Engineering, ETL Development, Database technologies (any RDBMS), Unix/Linux, Control-M.
Experience with DataStage or other ETL tools is required; knowledge of Neo4j is expected.
Work Experience Required: 12+ years in relevant Azure data support and engineering roles.
Experienced in supporting complex wealth management or financial data applications using Azure cloud data services and ETL tooling.
Able to operate cross-functionally, managing incident queues proactively and coordinating resolutions across multiple teams within SLAs.
Strategically focused on technical innovation, automation, and mentoring others to improve team capabilities and solution designs.