Hello! I'm Lokesh Reddy Venna, a passionate Data Engineer, Software Developer, and Machine Learning enthusiast. Currently, I'm pursuing a Master's in Data Science at the University of Maryland, Baltimore County, where I’m honing my skills in designing scalable data pipelines, developing robust software solutions, and applying machine learning models to solve complex business problems.
My academic background in Computer Science, coupled with hands-on experience in data engineering and software development, has equipped me with the technical expertise and problem-solving abilities needed to excel in fast-paced environments. I thrive on transforming raw data into actionable insights and building software that scales efficiently.
Master of Professional Studies in Data Science
University of Maryland, Baltimore County | Jan 2024 - Dec 2025
- GPA: 4.00/4.00
- Focus Areas: Data Engineering, Machine Learning, Big Data Processing, Advanced Database Management, LLMS, Neural Networks, Deep learning
- Key Coursework: Big Data Analytics, Advanced Machine Learning, Data Warehousing, Cloud Computing, Deep learning, Neural Networks, Statistical Methods in Data Science
Bachelor of Engineering in Computer Science
Amity University Rajasthan | Aug 2019 - Jun 2023
- GPA: 3.36/4.00
- Key Coursework: Python, Java, C++, SQL, Object-Oriented Programming, Data Structures and Algorithms, Software Engineering, Artificial Intelligence, Web Development
Certifications
- AWS Certified Data Engineer Associate: Mastered AWS services such as S3, Redshift, Glue, and Lambda to design and implement scalable data pipelines.
- Machine Learning & Data Science Specializations: Completed advanced courses on Coursera and LinkedIn Learning, focusing on predictive modeling, deep learning, and data engineering.
Data Engineer | Exavalu | Jan 2023 – Jan 2024
- Project: Smart Data Lake Insurance
- Role: Spearheaded the development of a big data platform, ensuring seamless data ingestion, transformation, and storage.
- Technologies Used: AWS Glue, AWS Lambda, AWS Stepfunctions, Apache Spark, AWS S3, Redshift, Python, Data quality, Data Modelling
- Achievements:
- Enhanced data pipeline performance by 40% using optimized Spark jobs and efficient data partitioning.
- Automated ETL workflows with Apache Airflow, reducing manual intervention by 50%.
- Improved query performance on large datasets by 30% through data modeling and indexing in Redshift.
Software Developer Intern | Exavalu | Jan 2023 – Apr 2023
- Project: Pharmacy Billing Management System
- Role: Developed a web application and implemented several functionalities and RESTful APIs for a scalable pharmacy management platform.
- Technologies Used: HTML, CSS, Javascript, Bootstrap, Jquery, Jdbc, Java, MVC, Spring Boot, Hibernate, MySQL, Docker
- Achievements:
- Reduced response time by 20% through efficient API design and database optimization.
- Implemented microservices architecture, enhancing system scalability and resilience.
- Collaborated with front-end developers to integrate APIs seamlessly, improving user experience by 25%.
Machine Learning Engineer Intern | Verzeo | Jul 2020 – Aug 2020
- Project: Red Wine Quality Prediction
- Role: Developed machine learning models to classify wine quality based on chemical properties.
- Technologies Used: Python, Pandas, Matplotlib, Seaborn, scikit-learn, PyTorch, Jupyter Notebook
- Achievements:
- Achieved a 95% accuracy rate using Linear regression Technique.
- Established a linear regression algorithm for a wine quality prediction project, attaining a 93.77% accuracy rate and delivering actionable insights for marketing strategies.
- Led a cross-functional team of 4 members to deploy a machine learning solution 25% faster, enhancing project delivery efficiency by 40%
Marketing Targets Data Warehouse for Campaign Analytics | UMBC | GitHub
- Overview: Architected a data warehouse to support targeted marketing campaigns, integrating data from multiple sources.
- Technologies Used: SQL Server, SSIS, Power BI, Python
- Impact:
- Developed predictive models that improved marketing effectiveness by 35%.
- Created dashboards that provided real-time insights into campaign performance, enhancing decision-making capabilities.
In-depth Analysis of Global Food & Agriculture Statistics | UMBC | GitHub
- Overview: Conducted a comprehensive analysis of global agricultural data to identify trends and inform strategic decisions.
- Technologies Used: Python (pandas, NumPy, Matplotlib, Seaborn)
- Impact:
- Improved the accuracy of trend predictions by 25% through advanced statistical analysis and data visualization.
- Provided actionable insights that were used to optimize supply chain decisions.
Smart Data Lake Insurance Project | Exavalu
- Overview: Designed and implemented a scalable data lake architecture to support large-scale data processing and analytics.
- Technologies Used: AWS S3, AWS Glue, AWS Lambda, Apache Spark, Redshift
- Impact:
- Enabled the company to handle 10x data growth with no degradation in performance.
- Reduced data processing times by 40% using optimized ETL pipelines and efficient data storage solutions.
- Programming Languages: Python, Java, C++, SQL
- Data Engineering: Apache Spark, Hadoop, AWS (S3, Redshift, Glue, Lambda), Azure Data Factory, Snowflake
- Machine Learning: scikit-learn, PyTorch, TensorFlow, Keras, Pandas, NumPy
- Software Development: Java, Spring Boot, REST APIs, Microservices, Docker, Kubernetes
- Data Analysis & Visualization: Power BI, Tableau, Matplotlib, Seaborn
- Cloud & DevOps: AWS, Azure, Jenkins, Git, Docker, Kubernetes
- Databases: MySQL, PostgreSQL, SQL Server, NoSQL (MongoDB, DynamoDB)
- Other Tools: Apache Airflow, Jupyter Notebook, Git, Jenkins, Postman
- Dean's List: Recognized for academic excellence during my MPS in Data Science, maintaining a 4.00 GPA.
- Top Performer Award: Awarded during my internship at Verzeo for exceptional contributions to machine learning projects and data analysis.
- LinkedIn: Lokesh Reddy Venna
- GitHub: Lokesh Reddy Venna
- Email: [email protected]