Senior Data Engineer
LocationHyderabad Knowledge Park Tower 2
Also inIndia (Hybrid)
Work modehybrid
Typefull-time
SenioritySenior
Experience4–8 yrs
DepartmentData Engineering & Operations
Company size1,001–5,000 people
PostedOct 8, 2026 · 4d ago
Verified live16h ago
At a glanceSummarised by Seekless from the posting.
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
Banking or Financial Services experience
Regulatory reporting platform support
Exposure to Snowflake, Databricks, and Azure Data Platforms
ITIL Foundation certification
Skills
SQL Server
Oracle
PostgreSQL
Snowflake
Azure Data Factory
SSIS
Informatica
Airflow
Microsoft Azure
Synapse Analytics
Azure Storage
SQL
Python
PowerShell
Shell Scripting
ServiceNow
Jira
Splunk
Dynatrace
Grafana
Azure Monitor
Databricks
Benefits
Health insurance
Flexible working
End Date
Friday 30 October 2026
Benefits
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.
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Conduct root cause analysis (RCA) and implement preventive fixes.
•
Support Incident, Problem, Change, and Service Request management processes.
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Participate in on-call and operational support rotations as required.
Data Platform Operations
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Support data warehouses, lakehouses, reporting, and regulatory data platforms.
•
Troubleshoot failures across databases, ETL tools, APIs, and cloud services.
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Validate data loads, reconciliations, and downstream data availability.
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Ensure platform reliability, performance, and operational readiness.
Monitoring & Reliability
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Monitor application health, data pipelines, and infrastructure performance.
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Manage alerts, dashboards, and observability tools.
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Proactively identify and automate recurring operational issues.
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Maintain service availability and operational KPIs.
Release & Change Support
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Support production deployments and release activities.
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Perform post-release validations and health checks.
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Collaborate with engineering teams during hypercare and transitions.
Data Quality & Governance
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Monitor data quality controls and investigate data issues.
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Support regulatory, audit, security, and governance requirements.
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Maintain support documentation, runbooks, and knowledge repositories.
Continuous Improvement
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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
Nice to have
•
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.
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Reduced incident volumes and faster resolution times.
•
Improved data pipeline reliability.
•
Successful production releases.
•
Increased automation and operational efficiency.
•
High stakeholder satisfaction.
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