Data Engineer | PepsiCo | BWTech | Ex Mu Sigma | Skilled in Cloud, Python, R, SQL, PowerBI, Spark | FMCG Supply Chain Engineer | Specialized in Data Pipelines, Data Transformation, and Advanced Analytic Solutions

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Resume

ManiTejaGunda_Data_Engineer.pdf

About Me

I’m a data engineering professional with over 5 years of experience building robust and scalable ETL pipelines across cloud environments. My work focuses on end-to-end pipeline development — from data ingestion and transformation to deployment and automation — using tools and languages such as Python, SQL, and Spark.

I specialize in designing and implementing efficient data workflows that support reporting, analytics, and real-time decision-making. Whether it’s optimizing data transformations, automating processes with CI/CD practices, or supporting business teams through dashboards and reports, I prioritize clean architecture and long-term maintainability.

Passionate about solving complex data challenges, I enjoy working on cloud-native systems that integrate well across platforms and scale with organizational growth. I’m always looking for opportunities to contribute to impactful projects, stay current with industry best practices, and help teams deliver high-quality data products.

Work Experience

Jan. 2024 – Present

Data Engineer - PepsiCo

Plano, TX, USA

End-to-End Root Cause Analysis System with Real-Time Ingestion

• Built and optimized scalable ETL pipelines for enterprise data integration using modern data processing tools, enabling reliable ingestion, transformation, and delivery across cloud data platforms.
• Led the development and deployment of automated workflows with CI/CD practices, ensuring performance tuning, data quality, and end-to-end monitoring for critical reporting systems.
• Collaborated cross-functionally to deliver business-ready datasets and dashboards, supporting advanced analytics and operational decision-making through efficient data modeling and transformation.

Sep. 2022 – Dec. 2023

Data Engineer - BWTech @ UMBC

Baltimore, MD, USA

Event-Driven ETL Architecture for Academic Records Management

• Designed and deployed end-to-end ETL pipelines to ingest and transform academic datasets using scalable cloud infrastructure. Utilized tools for data orchestration, transformation, and loading into enterprise storage systems to support analytics and reporting needs.
• Implemented data validation and quality checks using Python and SQL, automated through CI/CD workflows to streamline deployment and ensure reliability across development, testing, and production environments.
• Integrated structured and unstructured data sources, including real-time ingestion with event-driven services, into cloud data platforms. Documented the architecture using HLDs and runbooks, enabling seamless handoffs and maintainability for cross-functional teams.

June 2020 – July 2022

Data Engineer - Mu Sigma Inc.

Bengaluru, Karnataka, India

Real-Time Data Integration and Analytics

• Engineered scalable ETL pipelines to process both batch and streaming data from diverse sources, performing end-to-end data ingestion, transformation, and storage to support enterprise analytics and reporting initiatives.
• Automated data workflows and batch ingestion using Python and SQL, optimizing operational efficiency and ensuring seamless data delivery to centralized data warehouses and data lakes.
• Integrated real-time data ingestion using event-driven components and applied data quality rules and governance standards. Documented pipelines through runbooks and HLDs, contributing to maintainable, production-ready solutions.

June 2019 – May 2020

Data Analyst Intern - Virtusa.

Chennai, Tamil Nadu, India

Marketing Analytics Pipeline

• Developed and maintained data pipelines to ingest, cleanse, and transform structured business data, supporting campaign analysis and business reporting through scalable data lake and warehouse solutions.
• Built and deployed statistical models for marketing performance analysis using Python and distributed computing frameworks, with results integrated into real-time reporting systems via APIs.
• Automated model training workflows and dashboard refresh cycles using cloud-native orchestration tools and CI/CD practices, while documenting data lineage and metadata for auditability and governance.

Education

2022 - 2024

University of Maryland Baltimore County

Baltimore, MD

Masters in Data Science

2016 - 2020

SRM Institute of Science and Technology

Chennai, India

B. Tech in Information Technology

Skills