Jayadev Vurlugonda

About Jayadev Vurlugonda

I am a results-driven Data Engineer with 2.8 years of experience delivering scalable, cloud-based data solutions using Azure Data Factory, Databricks, and PySpark. My focus is on building high-performance ETL pipelines and modern Lakehouse architectures that empower organizations to unlock real-time insights and make data-driven decisions with confidence. Key AchievementsDesigned and deployed 20+ reusable ADF pipelines processing 50GB+ of data daily, improving efficiency and maintainabilityBuilt and optimized Delta Lake pipelines on Databricks, ensuring ACID compliance and accelerating analytics by 35%Reduced ETL runtimes by 98%(9 hours → 15 minutes) by eliminating upstream bottlenecksAutomated health check reporting with Python (Pandas, OpenPyXL), cutting manual effort by 90%Orchestrated complex workflows with Airflow and ADF, enhancing reliability and SLA complianceEstablished robust data validation frameworks, reducing post-load issues by 60%🧠 What I BringProven ability to deliver optimized, reliable solutions under tight deadlinesStrong business acumen to translate requirements into scalable data modelsPassion for clean, production-ready code and continuous improvement Looking AheadI am eager to grow in roles that involve cloud data architecture, advanced analytics, and real-time data platforms, contributing to impactful projects where data is a core business driver.Let’s connect if you’re looking for a hands-on Azure Data Engineer who blends deep technical expertise with a strong business mindset to create future-ready data solutions.

Experience

1. Data Engineer

   Wipro

   Mar 2023 — Present · Chennai, IN

   As a Data Engineer at Wipro, I work on designing, developing, and optimizing large-scale data pipelines using Azure Data Factory, Databricks, and PySpark to support real-time analytics and enterprise-wide reporting needs.Key Contributions: • Engineered and managed 20+ reusable ADF pipelines handling over 50GB of data daily—significantly improving development speed and pipeline scalability. • Migrated 100+ relational tables from on-prem SQL databases to Azure Data Lake using Python and Sqoop, reducing manual intervention by 40%. • Designed scalable ETL workflows in Azure Databricks using Delta Lake, ensuring ACID compliance and high-throughput processing. • Implemented a modern Lakehouse architecture to unify structured and semi-structured data, improving analytics speed by 35%. • Diagnosed and resolved upstream data issues, reducing ETL pipeline runtime by 98%(from 9 hours to 15 minutes). • Automated data health check reports using Python (Pandas, OpenPyXL), cutting manual effort by 90% and improving operational visibility. • Orchestrated complex workflows in Apache Airflow, decreasing failure rates by 70% through retry logic and real-time alerts. • Built reusable data validation frameworks for schema checks and profiling, lowering data quality issues post-ingestion by 60%. • Collaborated closely with cross-functional teams to deliver business-ready datasets aligned with stakeholder reporting requirements.

Education

• Kakatiya University, Warangal

  Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering

  2022

• Krishnaveni cooperative junior college

  12th Grade, Mathematics

• Kakatiya University

  Bachelor of Technology, Electrical, Electronics and Communications Engineering

• Triveni Talent School - India

  10th Grade, Mathematics