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Tier-1 brand, common data-engineer title, and metro hiring pool increase competition.
Core data engineering tools and ETL skills are broadly transferable across industries.
Senior role requiring specific ETL, cloud, and tooling expertise increases shortlisting strictness.
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Develop, support, and maintain ETL/ELT data pipelines and enterprise data engineering platforms, focusing on availability, reliability, and performance.
Provide L3 production assistance including incident management, root cause analysis, and resolution for data engineering operations.
Implement automation and operational improvements to enhance data integration processes and reduce manual intervention.
Experience in ETL/ELT development and support using SSIS, Apache NiFi, and cloud data integration technologies.
Proficiency with Google Cloud Platform (GCP) services, especially BigQuery, and enterprise workload automation tools like ActiveBatch.
Strong skills in SQL, query optimization, Python programming, and production support in a 24x7 environment.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in managing complex data engineering workflows across on-premises and cloud environments with focus on operational support and troubleshooting.
Capable of collaborating effectively with Data Engineers, Data Scientists, and Business teams to ensure data quality and analytic readiness.
Skilled in applying AI-assisted diagnostic tools and Agile/DevOps methodologies to improve incident resolution and support efficiency.