Pratik Lad

Results-driven Azure Data Engineer with 4.5+ years of experience in designing scalable data platforms and cloud-native data solutions on Microsoft Azure. Skilled in Azure Data Factory, Synapse Analytics, Azure SQL and Databricks. Extensive experience in building high performance ETL/ELT pipelines and enterprise data warehousing solutions.

Build production-grade Generative AI and LLM-powered automation workflows with Azure Functions and Python, transforming manual processes into intelligent, scalable systems. Passionate about delivering measurable business impact and innovation through data engineering and AI.

Software Engineer at LTIMINDTREE (2021-08 – 2022-08)

• Worked on Azure Data Factory (ADF) for creating pipelines, basic ETL workflows and moving data using Copy Activity for structured data ingestion.
• Built SQL queries in Azure SQL Database for data extraction, filtering, joins and basic reporting use cases.
• Managed structured and semi-structured datasets in Azure Data Lake Storage Gen2, enabling scalable and centralized data storage for analytics workloads.
• Developed basic data transformation workflows using ADF mapping concepts and simple data flows for preparing data.
• Created initial dashboards in Power BI to visualize business and operational metrics for reporting needs.
• Built simple automation workflows using Power Automate to reduce manual repetitive tasks and increase efficiencies.
• Monitored Azure Data Factory pipelines by analyzing activity runs to maintain 99.5% workflow reliability.

Software Engineer at LTIMINDTREE (2022-08 – 2025-08)

• Designed and developed scalable Azure Data Factory (ADF) pipelines with parameterization, dynamic content, linked services and triggers orchestration (schedule, tumbling window and event-based triggers) for enterprise data workflows.
• Built large scale data processing pipelines using Azure Databricks with Pyspark, data cleaning, transformations, aggregations and performance optimization on big datasets.
• Built robust production-grade Python scripts for data validation, automation, and end-to-end pipeline monitoring across data workflows.
• Designed end-to-end data ingestion and transformation pipelines using ADLS Gen2, Azure SQL DB, Azure Synapse Analytics, and Databricks for both batch and near real-time processing.
• Tuned performance in Azure SQL and Azure Synapse Analytics, including analysis of execution plans, indexing strategies, statistics optimization and deadlock resolution.
• Created small dashboards in Power BI to support business insights. Automated 5+ business workflows using Power Automate, reducing manual effort by approximately 40%.
• Troubleshot and fixed complex issues in ADF and Synapse pipelines by analyzing logs, dependencies tracking and execution flows debugging improved performance by 20%.
• Optimized Databricks (PySpark) workloads, identifying bottlenecks and improving execution efficiency for large scale data processing.

Senior Software Engineer at LTIMINDTREE (2025-08 – Present)

• Built an ML-based anomaly detection system to detect deviations in incident patterns and auto-generate cause summaries, driving proactive issue resolution and reducing escalations.
• Developed an AI-based Email Validation engine utilizing NER models to validate email communication content, detect data inconsistencies, and optimize deliverability rates.
• Designed and deployed serverless event-driven automation pipelines using Azure Functions connected to Azure data services.
• Developed production grade LLM workflows with Azure Open AI using RAG architecture for domain specific automation use cases.
• Built and optimized Power Automate workflows across multiple use cases, significantly reducing manual intervention and improving process efficiency.

M.Tech in Software Engineering – BITS Pilani (2025-10)

BSc in Computer Science – Ramniranjan Jhunjhunwala college (2021-05)