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Senior Data Engineer

Lloyds Technology Centre
Hyderabad, IND
Full-time
Senior · 4–8 years experience
Hybrid
Discovered 2 weeks ago
airflowazureazure-data-factorydatabricksdynatracegrafana

Full Job Posting

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.

Qualifications

  • 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.
  • 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.
  • 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.
  • Key Responsibilities
  • 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.

Preferred Qualifications

  • Preferred

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