I'm Akhil Kumar Reddy, a Senior Data Engineer and AI/ML Engineer with 6+ years of experience delivering data-driven, cloud-native solutions across healthcare, finance, and retail. I design scalable ETL/ELT pipelines, data lakes, warehouses, and ML workflows on AWS, Azure, and GCP, helping teams turn data into actionable insights. I specialize in real-time streaming, MLOps automation, data governance, and BI enablement, building end-to-end systems that drive both business impact and operational efficiency in multi-cloud environments. Proficient in Python, SQL, PySpark, dbt, Delta Lake, Snowflake, MLflow, LangChain, and modern orchestration and deployment tools, I’m passionate about turning complex data problems into robust, scalable solutions.

Akhil Kumar Reddy

I'm Akhil Kumar Reddy, a Senior Data Engineer and AI/ML Engineer with 6+ years of experience delivering data-driven, cloud-native solutions across healthcare, finance, and retail. I design scalable ETL/ELT pipelines, data lakes, warehouses, and ML workflows on AWS, Azure, and GCP, helping teams turn data into actionable insights. I specialize in real-time streaming, MLOps automation, data governance, and BI enablement, building end-to-end systems that drive both business impact and operational efficiency in multi-cloud environments. Proficient in Python, SQL, PySpark, dbt, Delta Lake, Snowflake, MLflow, LangChain, and modern orchestration and deployment tools, I’m passionate about turning complex data problems into robust, scalable solutions.

Available to hire

I’m Akhil Kumar Reddy, a Senior Data Engineer and AI/ML Engineer with 6+ years of experience delivering data-driven, cloud-native solutions across healthcare, finance, and retail. I design scalable ETL/ELT pipelines, data lakes, warehouses, and ML workflows on AWS, Azure, and GCP, helping teams turn data into actionable insights.

I specialize in real-time streaming, MLOps automation, data governance, and BI enablement, building end-to-end systems that drive both business impact and operational efficiency in multi-cloud environments. Proficient in Python, SQL, PySpark, dbt, Delta Lake, Snowflake, MLflow, LangChain, and modern orchestration and deployment tools, I’m passionate about turning complex data problems into robust, scalable solutions.

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Work Experience

Senior Data Engineer / AI-ML Engineer at OncoHealth
April 1, 2024 - Present
Architected and deployed end-to-end multi-cloud data pipelines integrating EHR, claims, pharmacy, and retail data using AWS Glue, Redshift, SageMaker, and GCP BigQuery. Built and deployed AI/ML models (PyTorch, Scikit-learn, BERT) for patient outcomes, fraud detection, and retail forecasting, improving prediction accuracy by 22%. Implemented real-time analytics pipelines using Kinesis, Pub/Sub, and Spark Streaming for healthcare claims and retail personalization. Automated ML lifecycle (data prep, model training, deployment) using Airflow, MLflow, and GitHub Actions, cutting manual steps by 40%. Deployed NLP-based insights systems leveraging BERT and LangChain to analyze patient feedback and pharmacy reviews. Delivered Looker and Tableau dashboards visualizing patient KPIs, financial metrics, and retail engagement trends. Ensured HIPAA and GDPR compliance through encryption, masking, and cross-cloud IAM controls.
Senior Data Engineer at Molina Healthcare
May 1, 2023 - March 1, 2024
Developed ADF + Databricks (PySpark) pipelines for claims and provider data, implementing Medallion architecture for scalable lakehouse design. Migrated legacy SQL workloads to Azure Synapse, improving reporting speed by 40%. Built ML models in Azure ML for patient churn and readmission risk, increasing retention by 15%. Automated ingestion pipelines via Event Hubs + Kafka, ensuring real-time availability of clinical data. Implemented governance with Azure Purview and CI/CD with Azure DevOps + Bicep, reducing deployment times by 30%. Created Power BI dashboards for executive-level insights on patient outcomes and cost optimization.
Data Engineer at Northern Trust
June 1, 2019 - December 1, 2022
Designed AWS Glue pipelines and optimized Redshift/Snowflake data marts for financial reporting and analytics. Built fraud detection pipelines using Kafka, Kinesis, and Spark Streaming integrated with SageMaker ML models. Automated CI/CD using Terraform, Lambda, and CodePipeline, reducing release cycles by 35%. Migrated on-prem SQL workloads to AWS Cloud, improving performance and cutting costs by 30%. Delivered Tableau and Power BI dashboards for real-time risk tracking and KPI visualization.

Education

Master of Arts in Information Technology Management at Webster University
January 11, 2030 - January 8, 2026

Qualifications

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Industry Experience

Healthcare, Financial Services, Retail