Senior Data Engineer · Dallas TX or Remote
Response: < 24 hours
Visa: H1B Transfer
Focus: DE · ML Eng · AI Platform
Location: Dallas TX or Remote

Hi, I'm
Narendranath Edara

Senior Data Engineer with 4+ years architecting production data platforms across Azure, Microsoft Fabric, and Databricks. Delivered 3-month to 14-day deployment cycles, 67% ETL cost reduction, and 98% uptime SLA on enterprise payroll infrastructure at scale.

85%
Faster Deploys
$4M
Annual Savings
98%
Uptime SLA
4.0
Master's GPA
View Projects Get in Touch Download Resume
Narendranath Edara
Data Engineer
4+ Years Experience
ML Engineer
NLP · AI Agents · LLMs
pipeline.py
Narendranath Edara
About Me

Data Engineer. Systems Thinker. Builder.

I started in analytics, building search engines at Zomato and forecasting supply at Udaan, then moved fully into engineering the infrastructure that makes analytics possible at scale. Today I design streaming data platforms, AI automation agents, and self-healing pipelines that run without hand-holding.

At ExponentHR I reengineered CDC-based ETL to cut batch runtimes from 30 min to under 8 min, compressed deployment cycles from 3 months to 14 days with CI/CD automation, and shipped AI agents that eliminated 15+ hours of manual sprint work, all while maintaining 98% uptime on production payroll systems.

Outside work I build production systems that scratch my own itch: JobScout scrapes 109 companies every 5 minutes and auto-matches jobs to 95+ tailored resumes, and AutoApply AI chains 5 LLM providers behind a Chrome extension so I never hit a rate limit. I hold a 4.0 GPA Master's from Missouri S&T and a peer-reviewed publication in Taylor & Francis 2025.

   Currently at ExponentHR · Open to Senior Data Engineer, ML Engineer, and AI Platform roles · Dallas TX or Remote

Technical Expertise

Languages
Python SQL T-SQL PySpark Bash R
Data Engineering
Apache Spark Kafka Databricks Airflow Delta Lake ETL/ELT Data Modeling SSIS
Cloud & Infrastructure
Azure (AKS, DevOps) Microsoft Fabric AWS (S3) Docker Kubernetes CI/CD Git
ML & AI
MLflow LangChain RAG Feature Engineering Model Serving NLTK spaCy
Tools & Observability
FastAPI Power BI DAX Elasticsearch Prometheus Grafana Streamlit
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 governed semantic layer on Microsoft Fabric with DAX metrics and AI agents translating business questions to SQL, cutting support tickets by ~40% and query response from 12s to under 4s
  • Compressed deployment cycles from 3 months to 14 days by owning CI/CD end-to-end through Azure DevOps, restructuring cross-team handoffs that accounted for 11 weeks of idle time
  • Reengineered CDC-based ETL from full-table reloads to incremental capture with merge upserts, cutting batch runtime from ~30 min to under 8 min and compute costs by ~67% by eliminating full-table I/O and data shuffling
  • Engineered one-click Azure DevOps pipeline with idempotent provisioning for Contained AAG databases (restore, security, recovery, listener validation, CDC), eliminating ~1 hour per request across 20+ daily copy-downs
  • Owned payroll-critical database recovery using containerized AAG failover, maintaining 98% uptime SLA with sub-hour restore targets including CDC capture job recovery after failover events
Microsoft Fabric DAX CDC/ETL Azure DevOps CI/CD SQL Server AI Agents
Aug 2023 - Jul 2024
1 Year
Missouri S&T

ML Engineer | Data Engineer

Missouri University of Science and Technology

Rolla, MO

  • Engineered Azure AI Anomaly Detector pipelines selecting optimal algorithms per time-series profile, achieving 95%+ accuracy — caught a production memory leak 4 hours before outage
  • Implemented tunable thresholds per service, filtering ~250 weekly non-actionable P3 alerts, moving signal-to-noise from 1:5 to 1:1.2 — ended alert blindness during on-call rotations
  • Migrated from static D-Series VMs to AKS with HPA, raising CPU utilization 12% to 64%, consolidating 20 nodes to 4-8 dynamic, cutting monthly Azure spend by $3,200
Azure AI AKS/HPA Python REST API Anomaly Detection Kubernetes
Jun 2023 - Aug 2023
3 Months
C2FO

Engineering Intern

C2FO

Leawood, KS

  • Conducted SQL analysis of B2B financial transaction patterns to identify user behavior trends and inform product prioritization
  • Authored data-driven PRDs that reduced development resource allocation time by 50% by eliminating spec ambiguity across cross-functional teams
  • Segmented user journeys across FinTech user types using data analytics to build targeted roadmaps for the preferred offers tool
  • Earned CSPO certification (Scrum Alliance) while collaborating with engineering, design, and business stakeholders in agile sprints
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

  • Built real-time competitor analytics platform tracking pricing, delivery times, and coverage, feeding pricing changes that contributed to 9% market share gain in contested metros
  • Optimized search relevance with ranking models using contextual signals (time, location, cuisine affinity), improving search-to-conversion across millions of daily queries
  • Built Elasticsearch enterprise search indexing 100K+ documents, reducing Support Desk volume by ~80% through self-serve query resolution
Elasticsearch SQL Competitor Analytics Ranking Models Search
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
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
JobScout

JobScout: Automated Job Discovery Platform

Zero-cost production platform scraping 109 company career pages across 6 ATS platforms (Workday, Greenhouse, Lever, iCIMS, Taleo, SmartRecruiters) every 5 minutes. Multi-signal relevance engine scores jobs on skills, location, experience level, and H1B sponsorship. 95+ tailored resumes indexed with TF-IDF cosine similarity — best-match auto-selected per job. Instant Discord + Telegram alerts for dream roles. Full application lifecycle tracker.

109
Companies
5min
Scrape Cycle
95+
Resumes
FastAPI React TF-IDF SQLite GitHub Actions

AutoApply AI: Chrome Extension + AI Backend

AI job application assistant combining a Chrome MV3 extension with a FastAPI backend on Fly.io + Supabase + Upstash Redis. 5-provider LLM chain: Anthropic Claude → OpenAI → Kimi → Ollama → keyword fallback — zero-downtime AI regardless of provider outages. TF-IDF cosine similarity engine matches job descriptions to the best resume from a 95+ PDF vault. Full auth via Clerk RS256 JWT. CI/CD via GitHub Actions.

5
LLM Providers
MV3
Chrome Ext
Live
Production
FastAPI PostgreSQL Redis LangChain Fly.io
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

85%
Faster Deployments
$4M
Annual Savings · Udaan
98%
Production Uptime SLA
95%+
Anomaly Detection Accuracy
73%
Faster ETL Runtime
4.0
Master's GPA · Missouri S&T
Get in Touch

Let's Connect

With expertise spanning streaming pipelines, cloud-native data platforms, and ML infrastructure, I focus on systems that deliver measurable outcomes at enterprise scale. If you're building something meaningful in Data Engineering, ML Engineering, or AI Platform development, I'm open to the conversation. Response time is under 24 hours.

Email

edara.narendranath@gmail.com

Phone

(573) 466-6656

Location

Dallas, TX, United States

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