Data Engineer

Actively Seeking Full-Time Roles Data Engineering • Analytics • Product Development • AI/ML Solutions
M.S. Business Analytics & Artificial Intelligence — The University of Texas at Dallas (Dean’s Excellence Scholar) Ex: Sabre | Capgemini | The Mohh
Tech Stack: Python • SQL • Power BI • Databricks • Azure • Snowflake • AWS • Tableau • Looker • LLMs • NLP • Agile

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About Me

I am a cross-functional data professional with 5+ years of experience spanning data engineering, analytics, and product development. I specialize in building scalable data pipelines, developing real-time dashboards, and applying AI/ML for measurable business outcomes. My work blends data architecture, business strategy, and execution to help organizations make faster, evidence-backed decisions.

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Featured Projects

BullsI — Anti-Cyberbullying App Designed and implemented a real-time NLP pipeline to detect harmful content in student communications, integrating automated alerts for school administrators. Deployed a data-driven pricing model that reduced incident management costs by $10K and maintained a 4.8/5 user rating.
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Marketly — Relocation Marketplace Architected the backend data model and analytics workflows for a two-sided relocation marketplace. Built SQL-based reporting pipelines to track user acquisition, engagement, and MoM growth (+10%). Achieved 5K+ active users through targeted campaign analytics.
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Healthcare Pricing Tool — Azure + Databricks Built a cloud-based ETL pipeline on Azure and Databricks to process and analyze 2.2M+ U.S. hospital pricing records. Developed aggregation logic and Power BI dashboards for cost transparency reporting across regions.
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Nike BI Dashboards — Customer Insights Developed data ingestion pipelines and designed business intelligence dashboards in Tableau and Power BI for marketing funnel, revenue segmentation, and user behavior analytics. Reduced manual reporting time by 35%.
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Customer Churn Prediction — Machine Learning Engineered an ML classification pipeline (logistic regression, decision trees, gradient boosting) using Python and SQL to predict customer churn. Achieved 80.7% accuracy and integrated results into retention strategy dashboards.
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SolarNet — Real-Time Solar Forecasting Built an AI-based image processing pipeline to analyze sky conditions and predict solar energy output for power grids. Achieved hourly prediction accuracy using deep learning models trained on historical image–weather datasets.
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LLM Multi-Tool Agent — Sabre Project Developed a LangChain-powered orchestration layer enabling an LLM to dynamically route tasks to specialized tools (calculator, code interpreter, web search, PDF summarizer). Deployed for internal data query automation and knowledge retrieval.
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Tech Stack

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Experience

Software Developer Intern

May 2024 – Aug 2024
  • Transformed raw multi-source travel datasets, including airline bookings and pricing, through optimized SQL queries, decreasing query run times by 30% and increasing overall data accuracy.
  • Engineered Power BI dashboards to visualize travel and booking KPIs within Sabre’s GDS, boosting internal data visibility by 35% and slashing stakeholder reporting time by 40%.
  • Analyzed 10+ slow-running SQL queries, pinpointed bottlenecks, and implemented performance enhancements, resulting in a 25% reduction in execution time and a measurable 40% improvement in data accuracy.
  • Automated Python pipelines and Power Query scripts, reducing manual workload by 30% and improving output consistency by 25%.
  • Delivered presentations to senior leadership on booking patterns and user behavior shifts, directly influencing a 15% increase in customer retention.
  • Mined travel booking data using SQL to identify friction points in checkout flow, leading to UI enhancements that improved booking completion rates by 12% weekly.

Senior Analyst

Jun 2021 – Jun 2023   • Pioneered SQL-based predictive models for user segmentation, enhancing campaign accuracy by 15% and generating $50K in additional revenue.
  • Developed Looker dashboards to visualize user engagement KPIs, increasing operational reporting efficiency by 25% company-wide.
  • Engineered SQL queries to locate 1,200+ high-value users weekly, enabling personalized marketing campaigns that boosted retention by 20% and improved customer lifetime value.
  • Built 10+ custom Tableau dashboards to visualize user behavior trends and campaign performance across diverse segments, supporting data-driven decision-making.
  • Partnered with operations to improve Python model validation workflows, increasing accuracy and reporting integrity by 95%.
  • Led roadmap and scope prioritization via JIRA to implement 5 key dashboard enhancements, improving data accessibility and reporting efficiency by 30%.

Co-Founder

Jun 2018 – Jun 2021
  • Modernized financial reporting with interactive Power BI dashboards tracking KPIs, providing insights that supported a $5M cost-reduction initiative.
  • Architected scalable data pipelines using SQL & Python to ingest and transform datasets exceeding 500M records, enhancing reporting capabilities and enabling data-driven decisions.
  • Delivered strategic presentations on patterns and behavior shifts to senior leadership, contributing to a 15% increase in customer retention.

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GitHub Stats

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Contact

LinkedIn: linkedin.com/in/sarthakmverma
Portfolio: sarthakmverma.github.io
Email: sarthak.verma@utdallas.edu