SQL Server DBA and Azure Data Engineer

Vineela Sadineni

***************@*****.*** 571-***-**** linkedin.com/in/vineela-sadineni

PROFESSIONAL SUMMARY

•Database Administrator and Developer with 4+ years administering and developing Microsoft SQL Server 2016, 2019, and 2022 databases, combining performance tuning, security, troubleshooting, deployments, automation, and data integration.

•Supports Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines, and migrated on-prem SQL Server to Azure SQL with schema assessment, validation, and cutover.

•Tunes with Query Store, Extended Events, and execution plans, cutting critical report runtime by up to 30%; builds SSIS and ETL solutions and automates monitoring across about 150 servers.

•Independently resolves complex database issues, cutting average resolution time by 25% on 24/7 on-call, and communicates clearly with developers and non-technical stakeholders.

CORE COMPETENCIES

SQL Server Administration

SQL Development

Azure

• SQL Server 2016/2019/2022

• SSMS, SQL Server Agent

• Install, Upgrade, Patching

• Maintenance Plans, Integrity Checks

• T-SQL Queries, Stored Procedures

• Functions, Views, Triggers

• CTEs, Window Functions

• PowerShell, Python Scripts

• Azure SQL Database

• SQL Server on Azure VMs

• Azure SQL Managed Instance

• Azure Monitor, Log Analytics

Performance & Monitoring

Security, HA & DR

ETL, Deployments & Docs

• Query Store, Extended Events

• Execution Plans, DMVs, Wait Stats

• Index & Statistics Tuning

• Redgate, Idera, SolarWinds

• Permissions, Auditing, Access Control

• Encryption, RLS, Entra ID

• Always On AG, Log Shipping, FCI

• Backup, PITR, DR Drills

• SSIS, Azure Data Factory

• Schema Changes, Production Releases

• Git, Azure DevOps CI/CD

• Runbooks, Relational Design

PROFESSIONAL EXPERIENCE

Database Engineering Intern Dec 2025 – Mar 2026

ImageWork Technologies Corporation

•Designed PostgreSQL databases for NYPD Line of Duty injury and approval tracking, supporting KPIs for approval cycle time, backlog, data accuracy, and case throughput.

•Validated Workday employee and organizational data, reconciling loads with row counts and primary-key checksums.

•Built a serverless AWS pipeline with Lambda and S3 triggers that reduced operational overhead by 50%, with IAM least-privilege access and CloudWatch monitoring.

Data Administrator – Consultant Jan 2021 – Dec 2024

Republic Services

•Administered, maintained, and supported SQL Server 2016, 2019, and 2022 across development, test, staging, and production, including installs, upgrades, patching, and post-upgrade validation.

•Monitored performance, availability, backups, and maintenance, managing SQL Server Agent jobs, maintenance plans, index rebuilds, statistics updates, and integrity checks.

•Troubleshot database, connectivity, and query performance issues using Query Store, Extended Events, execution plans, DMVs, and wait statistics; resolved blocking chains, deadlocks, and tempdb contention, and designed covering indexes that cut report runtime by up to 30%.

•Developed and optimized T-SQL queries, stored procedures, views, user-defined functions, triggers, and reusable scripts, and refactored long legacy procedures into smaller, commented units.

•Managed database security, permissions, auditing, and access controls, including least-privilege roles, Microsoft Entra ID authentication, column-level encryption, row-level security, and audit logging.

•Supported database deployments, schema changes, and production releases through change management, reviewing developers’ schema and code changes and deploying through Git and Azure DevOps CI/CD with rollback plans.

•Developed SSIS packages processing millions of records a day and Azure Data Factory pipelines for data integration, moving full reloads to incremental and CDC-based loads.

•Led data migrations, moving on-prem SQL Server to Azure SQL and leading a SQL Server-to-Snowflake migration with 60% faster queries, 45% lower cost, and 10x concurrent users.

•Supported Azure SQL Database, Managed Instance, and SQL Server on Azure VMs, monitoring with Azure Monitor, Log Analytics, Query Performance Insight, and Azure Backup.

•Managed full, differential, and log backups and point-in-time recovery, and implemented high availability and disaster recovery with Always On Availability Groups, failover cluster instances, log shipping, and DR drills.

•Automated recurring DBA, monitoring, and maintenance tasks with PowerShell, T-SQL, and Python across about 150 servers with threshold-based alerts, and cleaned up stale backup tables to cut storage costs by 20%.

•Resolved complex issues independently on a 24/7 on-call rotation, cutting average resolution time by 25%, and opened Microsoft support cases.

•Maintained runbooks, configuration records, and data dictionaries, gave database design guidance to developers, and explained technical issues to non-technical stakeholders.

ACADEMIC PROJECTS

Student Information Management System

Academic Project Java, JSP, Servlets, JDBC, SQL Server, HTML, CSS, JavaScript, Apache Tomcat

•Built a full-stack web application where students could register, enroll in courses, check attendance, and submit academic requests, while administrators managed records and approvals.

•Designed the SQL Server schema from scratch, with tables for students, courses, enrollments, and attendance, plus primary and foreign keys and constraints that blocked duplicate enrollments.

•Wrote stored procedures and optimized queries for enrollment, attendance, and record lookups, and connected them to the Java back end through JDBC.

•Added login and role-based access so students and administrators only saw the pages meant for them, then deployed and tested the app on Apache Tomcat.

U.S. Legislative Voting Analysis Spring 2026

Academic Project R, tidyverse (dplyr, stringr), readxl, Excel

•Worked with real LegiScan congressional data for a data capture and cleansing course, combining separate state files for roll calls, individual votes, legislators, and bills into one centralized dataset.

•Cleaned the data in R with mutate, filter, case_when, and str_trim: removed rows with missing IDs, trimmed stray spaces, standardized dates, and unified party labels spelled several different ways.

•Joined votes to roll calls and legislators with inner and left joins on their IDs, checking row counts after each join so nothing was silently dropped or duplicated.

•Added calculated fields for abstentions, vote direction, and cross-party votes, summarized the results by legislator, state, and party with group_by and summarise, built charts, and presented the findings.

EDUCATION

Master of Science in Computer Science GPA: 3.93/4.0 Jan 2025 – May 2026

Fitchburg State University, Fitchburg, MA

B.Tech in Computer Science & Engineering GPA: 3.5/4.0 Jul 2018 – Mar 2022

Vasireddy Venkatadri Institute of Technology

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