Akash Edara

Data Engineer

Hyderabad, Telangana, India4 yrs 9 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in building scalable data pipelines.
Proficient in cloud migration and data governance.
Innovative in developing AI-powered solutions.

Stackforce AI infers this person is a Data Engineer specializing in Healthcare analytics and cloud-based data solutions.

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Skills

Core Skills

Data EngineeringCloud PlatformsGen AiSoftware Engineering

Other Skills

DataBricksApache AirflowPySparkDelta LakeSnowflakeAzure Data FactoryETLData GovernanceLangChainLangGraphExtract, Transform, Load (ETL)MicroservicesAmazon Web Services (AWS)AI AgentsRetrieval-Augmented Generation (RAG)

About

I’m passionate about data engineering — building scalable data pipelines, transforming raw data into actionable insights, and enabling data-driven decision-making across teams. 🔍 What drives me: Solving real-world problems using data, optimizing pipelines for performance and reliability, and automating workflows that reduce manual effort. 💡 Core Competencies Programming & Scripting: Python | SQL Big Data & ETL: Apache Spark | Hadoop | Airflow | Snowflake | Apache Kafka | Apache Iceberg | Delta Lake | Data Modelling | Data Lakehouse Cloud Platforms: ☁️ Azure: Data Factory | Databricks | Data Lake | SQL DB ☁️ AWS: S3 | EC2 | Lambda Gen AI: 🧠 Generative AI & Prompt Engineering 🧬 Large Language Models (LLMs) 🔍 Retrieval-Augmented Generation (RAG) & Vector Databases 🤖 Agentic AI & MCP Architecture for Multi-Agent Systems 🧩 LangChain & LangGraph for building modular, multi-agent workflows DevOps & Automation: Docker | Kubernetes | Jenkins | GitLab | Azure DevOps | Terraform | Helm Databases: MySQL | PostgreSQL 📈 Always Learning I’m constantly exploring new tools, frameworks, and best practices in the data engineering space.

Experience

4 yrs 9 mos

Total Experience

4 yrs

Average Tenure

9 mos

Current Experience

Optum

Data Engineer

Jul 2025 – Present · 9 mos · Hyderabad, Telangana, India · Hybrid

Architected and optimized large-scale PySpark ETL pipelines processing 1TB+ data daily, delivering 99.9% data accuracy and high system reliability for enterprise healthcare analytics.
Led on‑prem to Azure cloud migration, designing end‑to‑end data workflows using Azure Data Factory and Databricks, enabling scalable, cost‑efficient data processing.
Implemented Medallion Architecture (Bronze, Silver, Gold) using Delta Lake, ensuring ACID compliance, schema enforcement, and improved data governance.
Replicated curated Gold layer datasets to Snowflake, significantly improving analytical performance and reducing downstream query latency for business and clinical insights.
Built a multi‑agent AI‑powered healthcare analytics chatbot using LangChain and LangGraph, enabling natural‑language interaction with structured healthcare data, intelligent task orchestration, and faster data‑driven decision‑making.

DataBricksApache AirflowPySparkDelta LakeSnowflakeAzure Data Factory+3