Akshay kumar Jangala
@akshaykumarjangala
Data Engineer specializing in AI-powered streaming pipelines and analytics for regulated industries.
What I'm looking for
I’m a Data Engineer with 3+ years of hands-on experience building AI-powered data systems and real-time streaming pipelines across healthcare and financial services. I focus on measurable outcomes—cost savings, faster decisioning, and reliable uptime across AWS, Azure, and GCP.
In my current role, I developed an NL-to-SQL chatbot using Azure OpenAI GPT-4o and Copilot Studio, enabling 50+ finance analysts to query Synapse and get auto-generated Plotly visualizations in Microsoft Teams. I also built AWS Bedrock validation agents that classify and route data quality exceptions, cutting manual review time and improving downstream accuracy, while maintaining 99.9% pipeline uptime.
I’ve engineered end-to-end pipelines for high-volume, time-sensitive workloads—handling 500K+ daily transactions with Kafka and Spark Streaming, and migrating legacy ETL to event-driven serverless architectures with AWS Glue, Lambda, and Step Functions. I bring strong governance and security experience (HIPAA, PCI-DSS, RBAC, encryption, monitoring/alerting) alongside practical tooling like Terraform, CI/CD, and data modeling techniques.
Experience
Work history, roles, and key accomplishments
Built an Azure OpenAI GPT-4o NL-to-SQL chatbot with Copilot Studio and a FastAPI backend for 50+ finance analysts, delivering auto-generated visualizations with sub-2-second responses. Led event-driven claims streaming with Kafka/Spark Streaming for 500K+ daily transactions, cutting claim turnaround from 72 hours to 24 hours and reducing monthly infrastructure costs by $40K while maintaining 99.9%
Developed Azure Synapse/Databricks data integration for credit card transactions across 12+ banking systems, cutting risk report generation time by 50% and automating ETL for 2M+ daily transactions with PySpark/Data Factory. Implemented CDC into Synapse to reduce latency from 6 hours to 15 minutes, enforced PCI-DSS/SOX governance via Purview and Key Vault, and improved query runtime from 3 minutes
Built automated GCP ingestion pipelines using Python and Cloud Functions to load 500K+ daily records into BigQuery, improving data availability by 40%. Optimized BigQuery SQL with partitioning/clustering to reduce query execution time by 30% and cut monthly costs by $15K, and delivered Dataflow ETL plus Tableau dashboards improving delivery timelines by 25% and campaign ROI by 20%.
Education
Degrees, certifications, and relevant coursework
Auburn University at Montgomery
Master of Science in Management Information Systems, Management Information Systems
Completed a Master of Science in Management Information Systems at Auburn University at Montgomery.
CMR Institute of Technology
Bachelor of Technology in Computer Science, Computer Science
Completed a Bachelor of Technology in Computer Science at CMR Institute of Technology.
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