Worked as a lead engineer on enterprise-wide SQL Server and Sybase infrastructure across production and development environments.

Defined and enforced enterprise data governance standards by establishing data ownership, process, and data quality rules using AWS Glue Data Catalog, AWS Lake Formation, and Microsoft Fabric Data Governance, ensuing consistent and trusted information across business functions.

Designed and implemented data quality frameworks with automated validation, profiling, and monitoring critical datasets using AWS Glue, Snowflake, and Microsoft Data Quality features, reducing reporting errors and increasing confidence in analytics-driven decision-making.

Migrated SQL Server 2022 on-prem to Azure SQL Managed Instance.

Migrated the on-premises SQL Server to Amazon RDS to meet development team requirements and implemented read replicas in the West Coast region to support high availability and disaster recovery.

Worked on setting up API-first with Snowflake in AWS to access Realtime Bloomberg data for internal applications.

Migrated on-prem SQL Server 2016/2019 instances to SQL Server 2022 using a combination of strategies, including AlwaysOn Availability Groups (Active-Active-Passive), log shipping, database mirroring, and replication.

Migrated Sybase to SQL Server via Heterogeneous replication.

Led the migration of SQL Server instances from standalone physical servers to VMware-based virtual machines, improving resource utilization and scalability.

Developed and maintained Azure DevOps pipelines for database CI/CD automation and streamlined deployments.

Created Azure Logic Apps for automating alerts, ticketing, and integration between Azure services and ITSM platforms.

Built dynamic Power BI reports using data from Azure SQL Database and Azure Data Factory to provide real-time, actionable insights.

Built Azure Data Factory pipelines for secure and scalable data movement between on-prem and cloud sources.

Designed Azure Automation runbooks for routine maintenance tasks and proactive resource monitoring.

Developed PowerShell scripts that automated monitoring of SQL Server, Sybase, and Azure resources, reducing manual checks and improving issue detection time.

Wrote PowerShell scripts to enable simplified and controlled failover/failback operations between two geographically separate data centers.

Designed and implemented robust disaster recovery strategies using AlwaysOn, log shipping, and database mirroring.

Implemented custom monitoring tools using PowerShell and Unix Shell to complement third-party systems.

Created and maintained stored procedures.

Proactively did performance tuning on slow-running queries.

Mentored junior DBAs and developers, driving internal knowledge-sharing and skill-building initiatives.

Led the migration of 15+ on-prem SQL Server instances to Azure SQL Managed Instance with zero data loss and minimal downtime.

Developed secure, serverless REST APIs that queried Snowflake using the Python connector, returning real-time Bloomberg market data.

Designed an enterprise-wide alerting framework using Logic Apps, cutting incident response time.

Led data engineering and database administration initiatives across SQL Server, Oracle, and Sybase environments, ensuring secure, highly available, and high-performance database infrastructure.

Successfully executed SQL Server upgrades (2008 → 2012) and Oracle migrations to 12c.

Implemented HA/DR strategies including SQL Server clustering, log sipping, transactional replication, Oracle RAC/Goldengate replication, and Sybase warm-standby.

Participated in bi-yearly DR failover and failback testing.

Worked on performance tuning of SQL statements and Stored Procedures.

Tuned database servers when required in SQL Server, Oracle, and Sybase.

Supported various IBM clients with Sybase, Oracle, and SQL Server.

Responsible for performance tuning of slow-running SQL statements.

Provided database support for multiple IBM clients across Sybase, Oracle, and SQL Server environments.

Worked on performance tuning, optimizing slow-running SQL statements to improve application efficiency and overall system performance.

Fine-tuned disaster recovery procedures so databases can be recovered faster.