Database Administrator - SQL Performance & Automation

JAYANTH KUMAR MALLIREDDY

DATABASE ADMINISTRATOR SQL PERFORMANCE DATA RELIABILITY & AUTOMATION

Kansas City, MO, USA +1-816-***-**** *************@*****.*** PROFESSIONAL SUMMARY

Database Administrator and SQL Support professional with 4 years of combined experience supporting database, application, data- management, and reporting environments using PostgreSQL, MySQL, MongoDB, SQL, Python, Linux/Unix, and Databricks. Experienced in SQL query optimization, indexing, performance monitoring, schema support, access management, database troubleshooting, data validation, root cause analysis, and workflow automation. Improved data-retrieval performance by approximately 20% through query and indexing optimization while developing reliable SQL/Python workflows that strengthened data integrity, reporting accuracy, and operational support. TECHNICAL SKILLS

Database Technologies: PostgreSQL, MySQL, MongoDB, Relational Databases, NoSQL Databases Database Administration: SQL Query Optimization, Performance Tuning, Indexing, Execution Plan Analysis, Database Monitoring, Database Health Checks, Schema Management, Data Integrity, Access Management, Roles & Permissions, Database Troubleshooting, Log Analysis

SQL & Automation: SQL, Python, Linux/Unix, JavaScript, Git, GitHub, REST APIs, Postman, Workflow Automation Production & Application Support: Production Troubleshooting, Root Cause Analysis, Incident Investigation, Application Support, Change Validation, Data Issue Resolution, Technical Documentation Data Quality & Governance: Data Validation, Data Cleansing, Data Reconciliation, Data Quality Assurance, Source-to-Target Validation, Structured Data Management, Confidential Data Handling Analytics & Reporting: Databricks, Power BI, Tableau, Microsoft Excel, KPI Reporting, Dashboard Development, Data Visualization PROFESSIONAL EXPERIENCE

UNIVERSITY OF MISSOURI–KANSAS CITY Aug 2022 – Dec 2023 Database Administrator — Application & Platform Support Kansas City, MO

• Optimized operational and reporting SQL across PostgreSQL and MySQL by refining complex queries, execution patterns, and indexing strategies, improving data-retrieval performance by approximately 20%.

• Monitored database and application performance using SQL analysis, system logs, query behavior, and data-quality indicators, identifying bottlenecks and resolving issues affecting system reliability and downstream reporting.

• Improved database efficiency by analyzing query execution, index utilization, table relationships, and recurring access patterns to identify opportunities for SQL and schema optimization.

• Supported relational schema structures, table relationships, constraints, and data-management standards to maintain data integrity and alignment with application and reporting requirements.

• Automated recurring validation, reconciliation, and reporting processes using SQL and Python, replacing repetitive manual checks with standardized workflows and improving operational consistency.

• Resolved database and application issues by tracing SQL behavior, system logs, source records, and downstream outputs, performing root cause analysis and coordinating corrective actions with technical and business stakeholders.

• Administered database-supported access requirements through role-based permissions and authorized data-access practices, strengthening confidentiality, consistency, and controlled use of operational information.

• Validated application and database changes by reviewing SQL results, source-to-target data consistency, schema dependencies, and reporting outputs before release or stakeholder use.

• Standardized database procedures, troubleshooting guidance, data structures, and recurring support workflows across 4 operational areas, improving documentation quality and knowledge transfer. UNIVERSITY OF MISSOURI–KANSAS CITY — UNIVERSITY LIBRARIES Jun 2024 – May 2026 Administrative Student Assistant — Data & Reporting Support Kansas City, MO

• Managed operational and constituent datasets through collection, cleansing, validation, reconciliation, and reporting while applying 4 core data-quality controls: accuracy, completeness, consistency, and integrity.

• Developed repeatable SQL and Excel workflows to organize datasets, analyze trends, validate records, and prepare reliable recurring reports for university stakeholders.

• Reconciled inconsistent records by comparing source information, investigating discrepancies, and validating business rules before data was incorporated into recurring reports.

• Converted raw operational information into structured datasets, analytical summaries, and Power BI/Tableau reporting outputs that improved stakeholder visibility into activities and trends.

• Standardized recurring data-processing procedures, validation steps, and technical documentation while maintaining confidentiality and university data-governance requirements. UMKC ATHLETICS — WOMEN’S VOLLEYBALL PROGRAM Jan 2024 – May 2026 Athletics Student Manager — Marketing, Events & Game Operations Kansas City, MO

• Maintained attendance data, event schedules, operational records, and reporting documentation supporting NCAA Division I athletics planning and post-event analysis.

• Validated time-sensitive event and operational information and organized recurring records into structured reporting packages for coaches, administrators, marketing staff, and event-operations teams.

• Coordinated information and operational requirements across 5 stakeholder groups, including coaches, student-athletes, administrators, marketing personnel, and event-operations teams. PROJECTS

Alumni & Constituent Analytics Dashboard SQL, Python, Power BI, Excel, Data Validation

• Built an end-to-end source-to-report workflow using SQL and Python to extract, cleanse, validate, join, transform, and reconcile data from multiple operational sources.

• Developed reusable SQL validation routines to identify duplicate, incomplete, inconsistent, and anomalous records before data was released for analysis and reporting.

• Created interactive Power BI dashboards that enabled stakeholders to analyze trends, investigate changes, and trace analytical findings back to validated source data.

• Documented data relationships, SQL logic, validation rules, KPI definitions, and processing procedures to improve repeatability and reporting reliability.

Kaboom — Personal Finance & Budgeting Analytics Application MongoDB, REST APIs, JavaScript, JWT, Git/GitHub

• Integrated MongoDB-backed application services with multiple REST API endpoints to retrieve, validate, process, and display financial information across budgets, income, expenses, and account activity.

• Implemented data-validation controls, exception handling, protected routes, and JWT-based authentication to strengthen application security, data integrity, and backend reliability.

• Resolved backend data discrepancies by validating MongoDB records, API responses, and dashboard outputs while collaborating with developers to maintain source-to-application consistency.

• Collaborated within a 4-member Agile development team using Git and GitHub for version control, issue resolution, testing, and controlled application changes.

Volleyball Performance & Player Benchmarking Analysis Python, SQL, Tableau/Power BI

• Analyzed player and match datasets using Python and SQL across 9 performance measures, including kills, hitting percentage, assists, digs, blocks, service aces, reception efficiency, attack errors, and points per set.

• Built structured datasets and reporting views in Tableau/Power BI to support player benchmarking, performance comparisons, and recurring trend analysis.

• Documented data sources, KPI definitions, analytical assumptions, validation procedures, and SQL methodology to improve transparency and reproducibility.

EDUCATION & CERTIFICATION

Bachelor of Science in Computer Science

University of Missouri–Kansas City Jan 2022 – May 2026 Databricks Certified Data Analyst Associate Databricks Dec 2025 Credential ID: 168638975

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