Suresh Nadipineni

Sr. SQL Server & PostgreSQL DBA with 12+ years of enterprise experience in database administration and large-scale database migrations across Azure, AWS, and RDS environments — supporting PostgreSQL, MySQL, Oracle, and SQL Server — performing current-state assessments, designing phased cutover strategies, and ensuring data integrity with minimal business disruption. 2019–2025 focus on SQL Server (2019+) schema-versioning and migration modernization using Liquibase-based idempotent deployments orchestrated through GitLab CI/CD pipelines.

Proven outcomes: 99.9% uptime across 100+ databases, 60% ETL cost reduction via Azure Data Factory automation, 40% security improvement, and 30% CPU reduction through query optimization. Deep expertise across banking, healthcare, and technology — managing mission-critical database infrastructure on Azure and AWS. Experienced cross-functional collaborator partnering with application teams, solution architects, and infrastructure partners to assess dependencies, coordinate testing and validation, resolve data discrepancies, and lead post-migration stabilization.

Proven in data governance policies, SOX and HIPAA compliance, regulatory requirements, disaster recovery, and audit-ready documentation. Now expanding into AI-integrated data infrastructure — deploying pgvector on PostgreSQL as vector database backbone for RAG applications, designing LLM-ready ETL pipelines via Azure Data Factory, and building event-driven AI data streams with Confluent Kafka. Bridging 12+ years of enterprise database mastery with modern GenAI data engineering practices.

Sr. SQL Server & PostgreSQL DBA at Key Bank (2025-04 – Present)

Database Migration | Azure & AWS

• Designed and managed Azure Data Factory (ADF) pipelines for automated ETL workflows, data migration, and cross-cloud data orchestration — reducing manual processing time by 60%.
• Conducted current-state assessment of source database structures, data volumes, and dependencies prior to migration execution — collaborating with application teams and infrastructure partners to design migration strategies.
• Integrated Confluent Kafka with SQL Server and PostgreSQL enabling real-time data streaming, event-driven architecture, and low-latency pipelines using Kafka Connect and Schema Registry.
• Configured Always On Availability Groups and Failover Clusters — achieving 99.9% uptime across 100+ mission-critical databases supporting banking operations.
• Managed Azure SQL Databases and Cosmos DB with Geo-Replication, automated backups, and high availability for real-time analytics applications.
• Performed PostgreSQL performance tuning using EXPLAIN/EXPLAIN ANALYZE, pgBouncer connection pooling, autovacuum, and index optimization at scale.
• Ensured SOX and HIPAA compliance by implementing audit trails, data access controls, Dynamic Data Masking (DDM), TDE, and database activity monitoring.
• Built AKS-based containerized database infrastructure with ARM Templates and GitHub Actions CI/CD — creating reproducible, MLOps-aligned deployment pipelines.
• Automated database maintenance, backup schedules, and health monitoring using PowerShell and Bash — saving 15+ hours/week of manual DBA effort.
• Deployed pgvector on PostgreSQL clusters enabling vector similarity search — providing the database backbone for Retrieval-Augmented Generation (RAG) AI applications.
• Extended ADF pipelines to include AI data preparation stages: text chunking, embedding-ready formatting, and structured output to Azure Blob Storage for LLM-based application consumption.
• Designed Kafka event-streaming architecture feeding real-time transactional data into AI model inference pipelines — enabling live fraud detection and anomaly analysis with sub-second latency.
• Collaborated with AI/ML engineering teams to optimize database schema and query patterns for high-throughput embedding storage and retrieval supporting LLM fine-tuning data pipelines.
• Designed GitLab CI/CD pipelines automating database migration workflows across build, export, and deployment stages, using fire-and-forget execution patterns for long-running, multi-terabyte data export jobs.
• Led SQL Server database migration and schema-versioning modernization (2019–2025), implementing Liquibase-based idempotent schema and object export/deployment processes across SQL Server 2019 and newer platforms — validating object existence prior to create/update to support repeatable, drift-safe, GitLab CI/CD-driven deployments.
• Automated BCP-based data export with encryption/decryption handling for secure, large-scale database migration to Azure SQL Database.
• Built asynchronous, non-blocking compatibility scanning into CI/CD pipelines using allow-failure and extended-timeout patterns to validate migrated database objects in the background.
• Extended PowerShell automation onto Kubernetes-based Linux runners, bringing traditional Windows-centric DBA scripting into containerized CI/CD pipelines.
• Ensured compliance with data governance policies and organisational standards across all migration and data engineering activities.

Sr. SQL Server & PostgreSQL DBA at State of CT (Health Care) (2022-08 – 2025-03)

Database Migration | On-Prem & AWS

• Administered 100+ SQL Server and PostgreSQL databases in on-prem and AWS environments.
• Implemented PostgreSQL replication and high availability to support HIPAA-compliant disaster recovery.
• Optimized database performance by tuning queries, indexes, and storage configurations.
• Automated maintenance plans including backups, index maintenance, and health checks.
• Migrated databases from on-prem to AWS EC2, RDS, and Amazon Aurora — including PostgreSQL, SQL Server, MySQL, and Oracle workloads — using AWS DMS and pg_dump/pg_restore, optimizing storage and cost efficiency.
• Designed phased cutover plans to minimise business disruption; implemented data transformation and load processes for migration pipelines ensuring accurate schema mapping between source and target platforms.
• Coordinated testing and validation activities with application owners and QA teams — resolving post-migration data discrepancies using automated row-count and checksum reconciliation scripts prior to cutover sign-off.
• Performed cross-platform migrations involving PostgreSQL, MySQL, Oracle, and SQL Server workloads — ensuring data integrity, schema/data type compatibility, and minimal business disruption across heterogeneous environments.
• Documented migration risks, mitigation plans, and regulatory compliance requirements throughout the migration lifecycle to support audit readiness and ongoing maintainability.
• Implemented disaster recovery strategies using AWS Backup, EC2 snapshots, and S3 Glacier.
• Configured Always On, Replication, and Log Shipping for business continuity