Mahesh Reddy Suram

Data Engineer with experience in Python, SQL, ETL-style data processing, warehouse management systems, database optimization, and analytics-ready data workflows. Skilled in cleaning, validating, transforming, and preparing structured datasets from operational and document-based data sources. Hands-on experience with PostgreSQL, SQL Server, REST APIs, data quality checks, reporting datasets, and Python-based automation.

Academic project experience in RAG, LLM-assisted document question answering, unstructured text processing, retrieval workflows, and privacy-aware data handling.

Teaching Assistant - Data Structures - Northern Arizona University - Flagstaff, AZ

(2025-08)

• Assisted professor in grading assignments, exams, and coding projects for graduate-level data structures coursework.
• Conducted office hours to help students understand arrays, linked lists, stacks, queues, trees, graphs, hashing, and algorithmic problem solving.
• Explained time complexity, memory usage, and efficient coding practices using Python-based examples.
• Supported development of lab assignments involving structured datasets, algorithm design, and real-world programming scenarios.
• Mentored students on debugging, code quality, object-oriented programming, and efficient data handling techniques.

Data Engineer - EARBOR - Hyderabad

(2023-08 - 2024-11)

Project: Warehouse Management Data Platform. Developed and maintained data processing workflows for a warehouse management platform supporting product tracking, order management, inventory visibility, and user activity reporting.

• Built Python-based data processing scripts to clean, validate, transform, and organize product, order, inventory, and warehouse user data.
• Designed and optimized PostgreSQL and SQL Server tables, queries, joins, indexes, and stored data access patterns, reducing average dashboard query time by approximately 35%.
• Created SQL queries and backend data logic to support warehouse dashboards used by approximately 120 warehouse staff and managers to track product availability, order status, and inventory movement daily.
• Supported ETL-style data handling by validating incoming product and order records, standardizing fields, handling duplicate records, and improving data accuracy before storage.
• Prepared analytics-ready datasets for warehouse managers to monitor inventory movement, product availability, order flow, and operational performance.
• Automated recurring data checks using Python and SQL to identify missing values, duplicate records, incorrect product mappings, and inconsistent order statuses, reducing data discrepancies in reporting datasets by approximately 25%.
• Worked with application stakeholders to understand reporting requirements, align warehouse data sources with dashboard needs, and document data flow logic for product, order, inventory, and user activity datasets.
• Supported secure data access workflows (OAuth2.0, JWT, AES, PBKDF2) and conducted unit testing, debugging, and peer code reviews to improve data accuracy and backend reliability.
• Created validation checks and test scenarios for Python and SQL data workflows to confirm data completeness, duplicate handling, field standardization, and reporting accuracy before release.

Data Science Intern - VERZEO - Hyderabad

(2021-05 - 2021-08)

• Learned Python, machine learning fundamentals, data preprocessing, and algorithmic problem solving through guided internship projects.
• Developed a 3D bin packing optimization project to improve item placement inside boxes and reduce unused space.
• Used heuristic and algorithmic techniques to evaluate packing order, space utilization, and placement efficiency.
• Cleaned and prepared sample datasets for model experimentation and project analysis.
• Supported project lifecycle activities from requirement understanding and implementation to testing and final presentation.

Master's - Computer Science - Northern Arizona University (2026-05)

Bachelor's - Computer Science - Geethanjali College of Engineering and Technology (2023-06)