Senior Data Engineer

End Date
Friday 30 October 2026
We Support Flexible Working – Click here for more information on flexible working options
Flexible Working Options
Hybrid Working
Job Description Summary
The Data Engineer will collaborate with the Data Operations, Software Engineers, Data Scientists, and Business SMEs to design, develop, integrate and test Data Product features on the product roadmaps to meet customer needs.
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.