Addla Chandra

About Addla Chandra

Who am I? Data Engineer | Azure | PySpark | ADF | Databricks | Terraform | SQL | Real-time Streaming I’m a results-driven Data Engineer with 5+ years of experience designing, developing, and optimizing scalable data solutions in cloud ecosystems, primarily Microsoft Azure. My passion lies in transforming raw data into powerful insights that fuel business decisions and drive innovation. At LTI Mindtree, I engineered distributed data pipelines with Azure Databricks and implemented real-time ingestion with Azure Event Hubs, enabling low-latency analytics and faster decision-making. I’ve automated infrastructure provisioning using Terraform and built CI/CD pipelines in Azure DevOps to accelerate and simplify deployment cycles. Known for improving PySpark job performance by 40% and reducing critical data incidents by 25%, I’m constantly focused on system reliability, scalability, and operational efficiency. My expertise spans: ETL pipeline development (batch + real-time) Azure Data Factory, Databricks, Blob Storage, Event Hubs SQL stored procedures, schema design & optimization PySpark performance tuning & distributed data processing Data governance (Unity Catalog), CI/CD (Azure DevOps), Terraform (IaC) Cross-functional collaboration & production support I thrive in dynamic, global environments where data is at the core of transformation. I\'m always eager to learn, solve complex data challenges, and contribute to building high-performance data systems that make a real-world impact. Let’s connect if you’re looking for someone who can build, scale, and optimize your data infrastructure with precision and purpose.

Experience

1. Senior Data Engineer

   LTIMindtree

   Oct 2023 — Present · Hyderabad, IN

   Client: Johnson & Johnson | Team Size: 10 Engineering and optimizing high-performance distributed data pipelines on Azure Databricks, enabling efficient processing of massive volumes of structured and unstructured data to drive actionable insights and business outcomes Streamlining deployment and release processes by automating CI/CD pipelines in Azure DevOps Improving PySpark job performance by implementing partitioning, caching, and dynamic resource allocation strategies, achieving a 40% reduction in processing time and driving faster data insights Employing Terraform to automate and standardize infrastructure provisioning spanning VMs, Blob Storage, and Databricks workspaces Implementing real-time data ingestion using Azure Event Hubs, significantly reducing data latency and empowering instant analytics for faster decision-making Enforcing secure data access and end-to-end lineage with Unity Catalog, ensuring compliance with regulatory standards & enhancing data governance across the platform

Education

• Narayana Junior College - India

  Board of Intermediate - BOI

  2012 — 2014

• Malla Reddy Engineering College

  Bachelor of Technology - BTech

  2014 — 2018