Hemanth Chaliki
Software Engineer • h****************@gmail.com • +19******541 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Software Engineer with 3+ years of experience designing scalable backend systems, microservices, and cloud-native data pipelines across AWS, Azure, and GCP. Proficient in Python, Java, C++ and Go; experienced building REST APIs, ETL/ELT pipelines, and observability-driven production systems. Skilled at optimizing database performance, implementing CI/CD, and delivering analytics-ready data products that improve reliability and business decisioning.
Technical Skills
Programming Languages: Python,Java,C++,Go,JavaScript,TypeScript
Web Technologies: REST APIs
Frameworks and Libraries: Spring Boot,Node.js,scikit-learn
Databases: SQL,MySQL,PostgreSQL,Oracle,MongoDB
Cloud and DevOps: AWS,Azure,GCP,Docker,Kubernetes,CI,CD Pipelines,ELK Stack
Testing: Unit Testing
Data and Analytics: Apache Spark,Databricks,ETL,ELT,BigQuery,Power BI,Tableau,KPI Reporting,Data Visualization
Tools and Methodologies: GitHub
Backend & APIs: Microservices,Event-Driven Architecture
Software Engineering Practices: Object-Oriented Design,Automated QA,Agile Development,Code Reviews
Work Experience
MoneyGram
USA
Software Engineer
Feb 2026 – Present
Provided data engineering, analytics, and reporting solutions for business operations, sales, and marketing using cloud-hosted ETL, Databricks, and BI tools.
Tech Stack: Python, SQL, Power BI, Databricks, AWS, Azure, REST APIs, ETL, ELT
- Developed Python automation scripts using pandas and Databricks to streamline data collection and transformation, reducing manual ETL effort by 30% and accelerating time-to-insight for business reporting.
- Designed and maintained SQL-driven data pipelines ingesting data from 5+ sources, implemented data validation checks and incremental loads to ensure analytics readiness and reduce downstream errors.
- Built REST API integrations to centralize third-party platform data using Python, improving data accessibility for analytics consumers and reducing manual aggregation time by 40%.
- Created interactive Power BI dashboards tracking 15+ KPIs across sales, marketing, and operations, enabling executive-level reporting and driving data-driven decisions across teams.
- Operated cloud processing environments across AWS, Azure, and Databricks to scale ETL workloads and improve pipeline reliability, lowering failed job rates and improving SLA adherence.
- Performed root-cause analysis on reporting discrepancies, implemented automated data quality alerts and reconciliation checks, improving data accuracy and stakeholder trust in production reports.
Adobe
India
Software Engineer
Jan 2021 – Jul 2024
Worked at Adobe, a software and digital media company, building backend microservices, product catalog and internal platforms to support high-throughput product and billing workflows.
Tech Stack: Python, Java, Spring Boot, React, Redux, TypeScript, Oracle, MySQL, AWS, Docker, Kubernetes, ELK Stack
- Designed and implemented a Python-based microservices product catalog system handling 2M+ daily requests across 10+ services; improved API response times by 40% and maintained 99.9% uptime through load balancing and caching optimizations.
- Optimized database performance for Oracle and MySQL by query tuning, indexing, and schema changes, cutting average query execution time by 45% and improving end-to-end application response by 35%.
- Architected and deployed an end-to-end Extended Care Management System with automated billing and delivery pipelines using Spring Boot and SQL, increasing operational efficiency by 35% and reducing patient care cycle time by 45%.
- Engineered a secure CSOS validation platform combining React front-end and Spring Boot REST APIs for real-time validation workflows; reduced order processing time by 60% and contributed to $1M+ in incremental annual revenue.
- Led frontend development for dashboards and user portals using React, Redux, and TypeScript to improve usability and stakeholder engagement, increasing adoption of internal tools by 40%.
- Established CI/CD pipelines and containerized deployments using AWS, Docker, and Kubernetes, enabling zero-downtime releases and reducing deployment time by 70%; implemented ELK-based observability to cut incident resolution time by 35%.
Projects
Distributed System Infrastructure
Tools Used: Python, SQL, Distributed Systems, ETL, ELT
- Built a scalable system platform serving 10,000+ users that used distributed processing and real-time data pipelines to support high-throughput workloads.
- Authored functional and design specifications for clustered architecture and implemented fault-tolerant pipelines with automated quality checks and monitoring to reduce operational overhead.
AI-Powered Restaurant Kiosks with LLM Integration
Tools Used: OpenAI APIs, RAG, Whisper, Python
- Implemented a self-ordering kiosk integrating LLMs via OpenAI APIs and a Retrieval-Augmented Generation pipeline to deliver context-aware responses and personalized recommendations.
- Integrated Whisper for speech-to-text input to enable natural language interaction, improving accessibility and user experience for kiosk customers.
Predictive Crime Analytics
Tools Used: Python, SQL, scikit-learn, Tableau
- Consolidated three decades of fragmented crime records into a cleaned, structured dataset for trend analysis and executive KPI reporting.
- Built predictive classification models with scikit-learn achieving 87% accuracy and surfaced insights through Tableau dashboards to inform cross-functional stakeholders.
Education
Northern Arizona University
Master of Science in Business Analytics • USA • Aug 2024 – Dec 2025
Jawaharlal Nehru Technological University Kakinada
Bachelor of Technology in Electronics & Communication Engineering • India • Aug 2019 – May 2023
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