Data Engineer Governance

AKASH REDDY BOLLAMPALLY

United States

+1-913-***-**** **************@*****.*** www.linkedin.com/in/akash-reddy-33387b263

Professional Summary

Data Engineer with 5 years of experience in designing scalable ELT pipelines and optimizing data architectures. Expertise in Python, PySpark, and SQL, with a focus on Apache Spark for batch and streaming ETL transformations and Change Data Capture. Skilled in ensuring robust data governance, high-quality outputs for analytics, and effective pipeline automation on AWS and Azure platforms. Committed to delivering reliable, enterprise-grade solutions that drive data-driven decision making.

Technical Skills

•Cloud & Big Data Platforms: Azure Databricks, AWS (S3, EMR, Glue, Lambda, Step Functions, IAM), Snowflake, Azure Data Lake, Azure SQL, SQL Server

•Languages & Frameworks: Python, PySpark, SQL/T-SQL, Spark SQL, REST APIs, Java, Scala

•ETL & Data Engineering Tools: Azure Data Factory (ADF), Kafka, Kinesis, Airflow, ETL/ELT Pipelines, Data Modeling, Data Validation, Data Lineage, Change Data Capture, Apache Hudi, Apache Griffin, AWS Deequ

•DevOps & Automation: GitHub Actions, Azure DevOps (ADO) Pipelines, CI/CD, Workflow Orchestration, Terraform (optional)

•Monitoring & Logging: Pipeline Monitoring, Data Quality Dashboards, Error Handling, Reconciliation

•Visualization & Reporting: Power BI (DAX, MDX), Excel Automation

•Data Governance & Compliance: HIPAA Compliance, Data Security, Data Documentation

•AI/ML Support: Generating clean datasets for ML pipelines, LLM & Predictive Analytics Support

Professional Experience

HCA Healthcare Feb 2025 - Present

Data Engineer Nashville, TN

•Designed and maintained scalable ELT pipelines on Databricks leveraging Apache Spark DataFrames and Medallion architecture, processing 500+ GB/day of healthcare data to support robust analytics and decision-making.

•Developed reusable pipeline logic and automated CI/CD workflows using Azure DevOps and GitHub, reducing deployment errors by

30%.

•Conducted code reviews and mentored offshore and junior engineers, enforcing engineering standards and documentation practices.

•Participated in sprint planning, design reviews, and proactive troubleshooting of data quality issues.

•Implemented data governance, lineage, and modeling frameworks, ensuring HIPAA compliance and pipeline reliability.

•Collaborated with AI/ML teams to provide clean, labeled datasets for predictive analytics and patient outcomes modeling.

•Explored modern data delivery tools, including GenAI and agent workflows, to optimize ETL processes.

•Maintained comprehensive pipeline documentation and communicated progress across business and technical teams.

CGI Mar 2024 - Jan 2025

Data Engineer San Diego, CA

•Built and optimized Python/SQL pipelines for structured and unstructured financial datasets in Azure and AWS environments.

•Developed and maintained reusable ETL frameworks and automated CI/CD deployment pipelines using GitHub Actions and Azure DevOps.

•Integrated data from multiple sources into enterprise systems, ensuring reliability and adherence to finance compliance standards.

•Developed REST APIs to facilitate integration between AI/ML workflows and enterprise datasets.

•Mentored offshore engineers and conducted code reviews, ensuring consistency in engineering standards.

•Implemented data validation, reconciliation, and transformation logic, improving financial data integrity by 30%.

•Participated in sprint planning and system design sessions, identifying potential data bottlenecks.

•Supported data modeling, lineage, and governance initiatives, preparing data for analytics and regulatory reporting.

LTIMindtree Jan 2021 - Jul 2023

Data Engineer Hyderabad / India

•Designed, developed, and maintained ETL pipelines using Python, SQL, and PySpark for both batch and streaming data in Azure and AWS environments, leveraging Apache Spark for efficient data transformations.

•Developed relational and NoSQL data models to support analytics, reporting, and customer-facing applications.

•Integrated datasets from multiple sources into CDP/RTCDP systems, enabling unified customer analytics.

•Collaborated with AI/ML teams to provide high-quality datasets for model training and evaluation.

•Implemented data quality checks, error handling, and reconciliation logic to ensure high data integrity.

•Built dashboards and reports in Power BI for monitoring pipeline performance, data quality, and operational metrics.

•Assisted in automating workflow processes and explored modern orchestration tools such as Airflow.

•Gained exposure to cloud platforms (Azure, AWS) and big data frameworks while contributing to backend modules under senior guidance.

Academics

University of Central Missouri

2025

Computer science

VNR VJIET

2023

Bachelors of Technology, Information Technology

Certifications

•AWS Certified Data Engineer

•Microsoft Certified: Azure Data Engineer Associate

•Code-Tantra: Advanced Python training course

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