Open to Data Engineer & ML Engineer Opportunities

Hi, I'm
Narendranath Edara

Data Engineer building scalable analytics platforms and AI automation solutions. I transform complex data challenges into production-grade systems that deliver intelligence directly to users.

21×
Faster SDLC
40%
Overhead Reduced
99.99%
Uptime SLA
4.0
Master's GPA
View Projects Get in Touch Download Resume
Narendranath Edara
Data Engineer
5+ Years Experience
ML Engineer
NLP & Analytics
Narendranath Edara
About Me

Building Intelligence at Scale

Data Engineer with expertise in designing and deploying scalable data platforms. Passionate about leveraging AI to tackle complex challenges. Specialized in transforming fragmented data ecosystems into unified analytics infrastructure that enables cross-functional teams to drive data-driven decision making.

With a Master's degree in Information Science & Technology from Missouri University of Science and Technology (4.0 GPA), I combine engineering depth with business acumen. My experience spans from Zomato in India to ExponentHR in the US, giving me a unique perspective on data challenges at scale.

Recently, I've focused on MLOps and AI automation, building end-to-end ML pipelines with Spark, Kafka, and Airflow, and designing AI agents that democratize data access for technical and non-technical teams alike.

   Reduced SDLC from 3 months to 14 days (21× faster) through architectural design, Adopting Agile Project management and DevOps automation.

Technical Expertise

Languages
Python SQL T-SQL R PySpark
Data Engineering
Apache Spark Kafka Databricks SSIS Airflow ETL/ELT Medallion Architecture
MLOps & ML
MLflow Feature Engineering LangChain RAG
Cloud & DevOps
Azure Microsoft Fabric AWS Docker Kubernetes CI/CD
ML & Analytics
FastAPI NLTK spaCy Power BI
Academic Background

Education

Missouri S&T

Master of Science in Information Science & Technology

Missouri University of Science and Technology

Rolla, MO Jan 2022 - Dec 2023 4.0 GPA
GVP

Bachelor of Technology in Mechanical Engineering

Gayatri Vidya Parishad College of Engineering

India 2013 - 2017
Career Journey

Professional Experience

Jul 2024 - Present
1+ Year
ExponentHR

ML Engineer | Data Engineer

ExponentHR

Addison, TX

  • Architected AI-powered embedded analytics platform on Microsoft Fabric, migrating legacy SQL to DAX-based semantic models, reducing client support volume by 40% and improving query performance by 3×
  • Owned end-to-end CI/CD infrastructure, compressing deployment cycles from 3 months to 14 days (85% faster), ensuring consistent data delivery to SSRS and Power BI systems
  • Reengineered CDC-based SSIS ETL pipelines to process incremental changes, reducing runtime by 70% and cutting compute costs by 30% while maintaining data freshness SLAs
  • Optimized SQL Server OLAP performance through star schema redesign (Dim & Fact modeling) and index tuning, reducing query latency by 20%
  • Designed AI-driven automation agents integrating Git and Azure DevOps OData APIs, eliminating 15+ hours/sprint of manual reporting
  • Led production recovery using containerized AAG failover, restoring systems in <1 hour and sustaining 99.99% uptime SLA
SQL Server SSIS/CDC Azure DevOps Data Modeling CI/CD Power BI AI Agents
Jan 2023 - Jul 2024
1.5 Years
Missouri S&T

ML Engineer | Data Engineer

Missouri University of Science and Technology

Rolla, MO

  • Engineered Azure AI Anomaly Detector pipelines using optimal algorithms for diverse time-series data, achieving 95%+ detection accuracy and enabling proactive alerting
  • Designed configurable REST APIs with customizable sensitivity thresholds, enabling dynamic anomaly detection tuning and reducing false positives by 40%
  • Deployed anomaly detection services on Azure Kubernetes Service (AKS) with auto-scaling policies, ensuring 99.9% availability and 50% infrastructure cost reduction
  • Published research on sentiment analysis as a tool for gathering visitor insights using NLTK, spaCy, and Hugging Face transformers
  • Applied TF-IDF, PCA, and clustering techniques (K-Means, DBSCAN) to segment review data for strategic insights
  • Spearheaded sentiment analysis using NLTK, spaCy, and Hugging Face's VADER for the Nixon Library, translating complex data into strategic insights
  • Created dynamic Power BI visualizations supporting strategic initiatives
  • Published research on sentiment analysis as a tool for gathering visitor insights from online review sites
Azure AI Kubernetes Python Hugging Face Power BI ML
Jun 2023 - Aug 2023
3 Months
C2FO

Engineering Intern

C2FO

Leawood, KS

  • Utilized SQL for deep data analysis on financial transaction patterns, enhancing product development and user segmentation
  • Achieved 50% reduction in resource allocation time by authoring data-driven Product Requirement Documents
  • Segmented user journeys using data analytics to develop targeted product roadmaps for FinTech solutions
  • Segmented user journeys and developed targeted product roadmaps for various user segments
  • Collaborated with cross-functional teams to craft user-centric preferred offers tool
SQL Product Management Data Analysis PRD
Sep 2020 - Mar 2021
7 Months
udaan

Business Intelligence Analyst | Supply

udaan.com

India

  • Built predictive demand forecasting models driving $4 million annual savings and 7% ROI improvement through optimized inventory allocation
  • Achieved 99.3% fulfillment rate through statistical capacity planning, managing end-to-end first mile to last mile operations and data-driven supply chain optimization
  • Developed automated ETL pipelines for financial modeling and strategic planning dashboards in Power BI
  • Designed ML-based demand prediction models to forecast metrics and assess business performance at scale
Forecasting Predictive Models Power BI SQL Supply Chain Analytics
Mar 2018 - Sep 2020
2.5 Years
Zomato

Business Analyst

Zomato

Hyderabad, India

  • Designed real-time data analytics platform for eCommerce and competitor insights, directly contributing to 9% increase in market share and enabling data-driven pricing strategies
  • Optimized search relevance algorithms using ranking models and contextual signals, improving search-to-conversion rates across millions of queries
  • Built Elasticsearch-powered enterprise search engine indexing 100K+ documents with intelligent ranking, reducing Support Desk workload by 80%
  • Created dashboards to visualize discount strategies and conducted A/B testing on marketing campaigns to drive revenue
  • Awarded "Meal for One Champion" for exceptional contributions to order growth and cost reduction
Elasticsearch SQL Ranking Models A/B Testing Real-time Analytics Agile
Portfolio

Featured Projects

Production-grade systems demonstrating enterprise-level engineering

Value at Risk Graphs

Real-Time Portfolio Risk Analytics

Data Engineering Foundation: Built end-to-end streaming data pipelines with Apache Kafka (47.8 TPS) and Spark Structured Streaming for 5-second windowed aggregations. ML Integration: VaR calculations at 95% and 99% confidence levels with historical simulation methodology. Production-Ready: FastAPI REST API, Streamlit dashboard, and containerized infrastructure.

47.8
TPS
15K+
Records
<5s
Latency
Kafka Spark FastAPI Docker
Grafana Dashboard

Real-Time Fraud Detection Platform

ML Engineering Showcase: Production-grade ML platform with Apache Kafka event streaming (100+ TPS), LightGBM classifier, and MLflow experiment tracking. Data Pipeline: End-to-end pipeline from ingestion to prediction with exactly-once processing. DevOps: Prometheus + Grafana monitoring, containerized infrastructure, and Airflow orchestration.

100+
TPS
<1ms
Latency
MLOps
Pipeline
Kafka MLflow FastAPI Grafana
DBSCAN Clustering

Sentiment Analysis Research Platform

NLP Research: Comparative analysis of sentiment classification methods including VADER lexicon and RoBERTa transformers on Yelp/TripAdvisor reviews. ML Pipeline: Full preprocessing pipeline with text cleaning, feature extraction, and model evaluation. Research Publication: Published findings on ensemble approach combining rule-based and deep learning methods.

92%
Accuracy
5+
ML Models
Pub
Research
Hugging Face NLTK spaCy K-Means

AI-Powered Analytics Platform

Enterprise Data Engineering: Architected semantic layer over complex multi-schema SQL Server data warehouse enabling natural language querying. AI Integration: Built AI agents that translate business questions into optimized SQL, reducing report development overhead by 40%. Production Impact: Accelerated SDLC from 3 months to 14 days (21× improvement).

40%
Overhead Cut
21×
Faster SDLC
AI
Agents
Azure Power BI SQL Server SSIS
twitter vs twitch followers correlation

Game Downloads Prediction (R)

Statistical Modeling: Time series forecasting of mobile game downloads using R, comparing ARIMA, exponential smoothing, and regression models. Data Pipeline: Automated data collection and preprocessing pipeline. Business Impact: Actionable insights for marketing campaign timing and inventory planning.

3+
Models
R
Language
Time
Series
R Time Series ARIMA Forecasting

Web Scraping & Data Collection

Data Engineering Fundamentals: Automated data collection pipelines using Python, BeautifulSoup, and Selenium for large-scale web scraping. ETL Pipeline: Data cleaning, transformation, and storage workflows. Foundation: Core skills enabling data-driven ML projects through reliable data acquisition.

Auto
Pipeline
ETL
Process
Scale
Data
Python BeautifulSoup Selenium Pandas
Credentials

Certifications

DP-700 CERTIFIED

DP-700: Fabric Data Engineer Associate

Microsoft

2026

Azure AI CERTIFIED

Azure AI Fundamentals (AI-900)

Microsoft

2024

Azure AI ACCREDITED

Databricks Generative AI Fundamentals

Databricks

2026

Data Warehouse in Microsoft Fabric

Microsoft Applied Skills

SQL (Advanced)

HackerRank

Jira Fundamentals Badge

Atlassian

Certified Scrum Product Owner

Scrum Alliance

Academic Work

Research Publication

Peer-Reviewed Journal

An Examination of Sentiment Analysis as a Tool for Gathering Visitor Feedback

Dr. David Bojanic, Narendranath Edara, Jane Zhang

Journal of Nonprofit & Public Sector Marketing
2025
Taylor & Francis
View Publication
Testimonials

What Colleagues Say

View All on LinkedIn
Impact

Key Achievements

21×
Faster SDLC Delivery
200%
Revenue Growth at Zomato
$4M
Annual Savings at Udaan
99.99%
System Uptime SLA
45%
Release Cycle Reduction
4.0
Master's GPA
Get in Touch

Let's Connect

I'm actively exploring Data Engineer and ML Engineer opportunities where I can build next-generation analytics and AI platforms. If you share a passion for building systems that matter, I'd love to connect!

Email

edara.narendranath@gmail.com

Phone

(573) 466-6656

Location

Dallas, TX, United States

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