Talapaneni usha

[email protected] • +919515438795

PROFESSIONAL SUMMARY

Results-driven Data Engineer with 4 years of expertise in SQL and Python, specializing in designing optimized queries, automating data pipelines, and ensuring data integrity across large-scale datasets. Proven track record of improving data processing efficiency by 30% through workflow automation and delivering accurate, actionable insights to support strategic business decisions. Adept at collaborating with cross-functional teams to maintain high data quality standards and drive continuous improvement in data management practices.

WORK EXPERIENCE

Software engineeer

09/2022 - Present

[24]7.ai , Banglore

• Data Engineering Projects (SQL & Python):

• Developed ETL workflows using Python and SQL to ingest, transform, and load structured data from multiple sources

• Performed data transformations using SQL joins, aggregations, filtering, and deduplication

• Automated end-to-end data processing pipelines using Python for both file-based and database-driven data

• Optimized SQL queries, improving query performance and reducing processing time by 30%

• Collaborated with cross-functional teams to identify data issues and resolve performance bottlenecks

• Ensured seamless data flow and high data quality through validation, reconciliation, and monitoring processes

• Automation Script Development (Python & SQL):

• Designed and optimized automation scripts using Python and SQL, improving data processing speed by 40% and reducing error rates by 25%

• Automated manual data processing tasks using Python, reducing manual intervention by 30% and improving operational efficiency

• Implemented data validation checks to ensure record count accuracy and data consistency across datasets

• Built robust error handling and logging mechanisms in Python scripts to improve pipeline reliability and troubleshooting

• Optimized SQL queries for faster execution and improved data retrieval performance

Software engineer

08/2021 - 08/2022

Mithra info technology , Banglore

• SQL Queries and Stored Procedure Optimizations

• Wrote complex SQL queries to extract, manipulate, and analyze large datasets. Optimized storedprocedures, cutting execution time by 60%. Collaborated with teams to resolve performance bottlenecks.

EDUCATION

Bachelor of technology

07/2017 - 06/2021

Priyadarshini college of Engineering , Nellore GPA: 7.0

SKILLS

Technical Skills: SQL, Joins, Subqueries, Common Table Expressions, Window Functions, Aggregations, Filtering, SQL Query Optimization, Python, MySQL, MS SQL, Pandas, ETL Processes, Batch Data Processing, Data Transformation, Data Standardization

Soft Skills: Analytical Thinking, Problem Solving, Attention to Detail, Time Management, Collaboration

Tools: MySQL Server, Microsoft SQL Server, Jupyter Notebook, Git, VS Code

Other: Data Engineering, Software Engineering, Agile Methodology

PROJECTS

Automated Data Processing & ETL Pipeline (Python & SQL)

Technologies: SSMS and python IDLE

• Designed and implemented ETL workflows using Python and SQL to ingest, transform, and load structured data

• Automated end-to-end data processing for file-based and database-driven datasets

• Performed data transformations including joins, aggregations, filtering, and deduplication using SQL

• Implemented data validation and reconciliation checks to ensure data accuracy

• Optimized SQL queries, reducing processing time by 30%

2. Automation Script Development for Data Validation

• Developed Python automation scripts to replace manual data processing tasks

• Implemented error handling and logging mechanisms to improve pipeline reliability

• Reduced manual intervention by 30% and improved processing efficiency

• Ensured record count accuracy and schema consistency across datasets

3. SQL Performance Optimization Project

• Analyzed slow-running SQL queries and identified performance bottlenecks

• Optimized queries using indexes, query restructuring, and efficient joins

• Improved query execution performance by 30–40%

• Supported reporting and analytics teams with faster data availability

ACHIEVEMENTS

• Improved data processing performance by 40%

• Reduced data errors by 25%

• Reduced manual effort by 30%

• Optimized SQL queries by 30%

• Delivered high-quality, validated datasets

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