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Strong Tier-1 brand, metro location, and generalist senior data role with broad requirements increase competition.
Core data engineering skills transfer across industries, but market-data and client-support context increases domain specificity.
Mandatory tech stack (Python, Airflow, ETL, Linux) and domain experience plus US shift raise selection strictness.
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Own technical support and issue resolution for data ingestion, transformation, and delivery pipelines in global financial data environments.
Manage and monitor batch processing workflows, automation jobs, and troubleshoot failures to ensure pipeline stability and performance.
Collaborate with clients and engineering teams to analyze incidents, identify root causes, and drive resolutions or escalate as needed.
Strong Python programming skills with object-oriented application experience.
Experience with job scheduling and workflow tools such as Jenkins, Rundeck, or Apache Airflow.
Background in batch data processing, ETL pipeline development, and Data Lake architecture.
Availability to work US shift hours from 6:30 PM to 3:30 AM IST.
Senior associate level with expertise at the intersection of data engineering, operations, and client support.
Experience working in large-scale automated data environments requiring reliability and performance optimizations.
Comfortable operating Linux environments and handling version control using Git in fast-paced financial data contexts.