Senior Data Engineer

End Date

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Job Description Summary

Job Description

Data Engineer – BAU Operations & Support

Location: India (Hybrid)
Department: Data Engineering & Operations
Experience: 9+ Years

Role Summary

We are looking for a proactive Data Engineer – BAU Operations & Support to manage and support enterprise data platforms, ETL pipelines, regulatory reporting solutions, and cloud-based data services. The role focuses on ensuring platform stability, resolving production issues, maintaining data quality, supporting releases, and driving operational excellence across business-critical data ecosystems.

Key Responsibilities

Production Support & Incident Management

• Monitor and support ETL jobs, batch processes, and data pipelines.
• Investigate and resolve production incidents within agreed SLAs.
• Conduct root cause analysis (RCA) and implement preventive fixes.
• Support Incident, Problem, Change, and Service Request management processes.
• Participate in on-call and operational support rotations as required.

Data Platform Operations

• Support data warehouses, lakehouses, reporting, and regulatory data platforms.
• Troubleshoot failures across databases, ETL tools, APIs, and cloud services.
• Validate data loads, reconciliations, and downstream data availability.
• Ensure platform reliability, performance, and operational readiness.

Monitoring & Reliability

• Monitor application health, data pipelines, and infrastructure performance.
• Manage alerts, dashboards, and observability tools.
• Proactively identify and automate recurring operational issues.
• Maintain service availability and operational KPIs.

Release & Change Support

• Support production deployments and release activities.
• Perform post-release validations and health checks.
• Collaborate with engineering teams during hypercare and transitions.

Data Quality & Governance

• Monitor data quality controls and investigate data issues.
• Support regulatory, audit, security, and governance requirements.
• Maintain support documentation, runbooks, and knowledge repositories.

Continuous Improvement

• Develop automation scripts to reduce manual effort.
• Improve monitoring, recovery, and operational processes.
• Drive service stability, efficiency, and operational excellence.

Required Skills

Technical

• Databases: SQL Server, Oracle, PostgreSQL, Snowflake
• ETL & Integration: Azure Data Factory, SSIS, Informatica, Airflow
• Cloud: Microsoft Azure, Synapse Analytics, Azure Storage
• Programming: SQL, Python, PowerShell, Shell Scripting
• Monitoring Tools: ServiceNow, Jira, Splunk, Dynatrace, Grafana, Azure Monitor

Functional

• Production Support & Incident Management
• Data Pipeline Troubleshooting
• Root Cause Analysis (RCA)
• Data Quality & Reconciliation
• ITIL Service Management
• Regulatory Reporting Support

Qualifications & Experience

Essential

• 4-8 years' experience in Data Engineering, Data Operations, or Production Support.
• Strong SQL and troubleshooting skills.
• Experience supporting enterprise data platforms and ETL processes.
• Knowledge of incident, problem, and change management.
• Strong analytical, communication, and stakeholder management skills.

Preferred

• Banking or Financial Services experience.
• Regulatory reporting platform support.
• Exposure to Snowflake, Databricks, and Azure Data Platforms.
• ITIL Foundation certification.

Success Measures

• SLA adherence and platform availability.
• Reduced incident volumes and faster resolution times.
• Improved data pipeline reliability.
• Successful production releases.
• Increased automation and operational efficiency.
• High stakeholder satisfaction.