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Tier-1 brand, metro location, and broad data and stakeholder skillset increase applicant competition.
Core ETL and data engineering skills are broadly transferable across industries.
Mandatory Databricks/PySpark, SQL and senior-level ownership imply moderately strict technical and experience filters.
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Own and deliver timely and efficient ETL support, managing multiple ETL loads across diverse clients and industries.
Drive reduction in average response times and improvement in SLAs through root cause analysis, automated process enhancements, and innovative resolution approaches.
Manage and mentor sub-teams to meet client expectations and maintain strong stakeholder relationships through effective communication and feedback integration.
Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Engineering, Mathematics, Operations Research); ME/MTech preferred.
Hands-on experience with RDMS technologies, preferably Microsoft SQL Server, Databricks, or PySpark, plus at least one scripting language (VB Script, Perl, Python).
Excellent English communication skills (oral and written); demonstrated quantitative and technical expertise.
Work Experience Required: Not explicitly mentioned in the JD.
Experience in managing ETL processes and providing quick failure resolutions in high-impact, client-facing projects.
Able to bridge business, data management, and technical teams, quickly grasping business use cases to identify technical solutions.
Demonstrated ability to innovate, think critically, oversee quality control, and handle multiple competing priorities in a global team environment.