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Strong Tier-1 brand, generalist senior data engineer role, common skillset increases candidate competition.
Core ETL and Airflow skills are transferable, but financial market data domain raises moderate specialization.
Multiple mandatory technical skills and US-shift requirement raise screening but no explicit years stated.
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Provide technical support and issue resolution for global financial clients across large-scale data ingestion, transformation, and delivery pipelines.
Manage and monitor batch processing workflows, job schedules, and troubleshoot automation failures to ensure pipeline reliability and performance.
Collaborate with engineering teams and clients to analyze incidents, identify root causes, drive resolutions, or escalate as necessary.
Proficient in Python with experience building and maintaining object-oriented applications.
Experience with job scheduling and workflow tools such as Jenkins, Rundeck, Apache Airflow, or similar.
Background in batch data processing and working with ETL pipelines and Data Lake architectures.
Work US shift hours: 6:30 PM – 3:30 AM IST. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in supporting critical data operations in financial or large-scale automated data environments with a focus on pipeline stability and performance.
Comfortable working in an operational role sitting at the intersection of data engineering, client support, and troubleshooting under US shift timings.
Skilled in collaborating across cross-functional engineering teams and interfacing directly with global financial clients to resolve technical issues.