Headline

𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬 | 𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐅𝐚𝐜𝐭𝐨𝐫𝐲 | 𝐏𝐲𝐒𝐩𝐚𝐫𝐤 | 𝐃𝐞𝐥𝐭𝐚 𝐋𝐚𝐤𝐞 | 𝐀𝐃𝐋𝐒 𝐆𝐞𝐧𝟐 | 𝐄𝐓𝐋 | 𝐒𝐐𝐋 | 𝐈𝐦𝐦𝐞𝐝𝐢𝐚𝐭𝐞 𝐉𝐨𝐢𝐧𝐞𝐫

About

Azure Data Engineer with 4+ years of experience designing, developing, and implementing scalable cloud data solutions using Microsoft Azure technologies. Experienced in building enterprise-grade ETL/ELT pipelines using Azure Data Factory, Azure Databricks, PySpark, Delta Lake, and Azure Data Lake Storage Gen2. Skilled in designing modern Lakehouse architectures using Medallion Architecture (Bronze, Silver, Gold) to support analytics, reporting, and business intelligence solutions. Technical expertise includes: • Azure Data Factory pipeline development and orchestration • Azure Databricks and PySpark transformations • Delta Lake and Lakehouse Architecture • Azure Data Lake Storage Gen2 (ADLS Gen2) • Incremental loading, Watermarking, CDC and Schema Evolution • SQL development, optimization and data modeling • Star Schema, Fact and Dimension tables • SCD Type 1 and SCD Type 2 implementation • Azure SQL Database • Power BI analytical dataset preparation • Azure security using RBAC, Azure Key Vault and Managed Identity • Git, Azure DevOps and Agile/Scrum methodologies I have hands-on experience designing production-grade data pipelines, optimizing Spark workloads, migrating enterprise data platforms to Azure, and delivering reliable data solutions for analytics teams. I enjoy solving complex data engineering challenges and building scalable cloud data platforms that enable faster and smarter business decisions. Open to opportunities in: Azure Data Engineering | Cloud Data Platforms | Databricks Engineering | Data Platform Consulting

Location

Gurugram

Work experience

Senior Analyst - Azure Data Engineer at Virtusa, Jan 2024 - Nov 2025 · 1 yr 11 mos, Gururgram, Worked as an Azure Data Engineer designing and delivering enterprise-scale cloud data solutions using Azure Data Factory, Azure Databricks, PySpark, Delta Lake, and ADLS Gen2. Responsible for building scalable ETL/ELT pipelines, implementing Lakehouse architecture, and enabling analytics-ready data platforms. Key Responsibilities & Achievements: • Designed and developed end-to-end Azure Data Lakehouse solutions using Medallion Architecture (Bronze, Silver, Gold) with Delta Lake on Azure Data Lake Storage Gen2. • Built and maintained scalable ETL/ELT pipelines using Azure Data Factory and Azure Databricks for ingesting structured and semi-structured data from databases, APIs, and cloud storage. • Developed PySpark transformation frameworks for complex data processing, data cleansing, validation, and business rule implementation. • Implemented incremental loading strategies including watermark-based ingestion and CDC patterns to efficiently process high-volume datasets. • Created parameterized and reusable ADF pipelines using activities such as Copy Data, Lookup, ForEach, Execute Pipeline, and Stored Procedures. • Optimized Databricks workloads using Spark optimization techniques including partition pruning, broadcast joins, caching, and Delta Lake optimization, improving processing performance. • Designed analytical data models using Star Schema, Fact and Dimension tables, and implemented SCD Type 1 & Type 2 logic for historical tracking. • Implemented enterprise security using Azure Key Vault, RBAC, and Managed Identities for secure data access. • Monitored production pipelines, performed troubleshooting, and resolved data processing issues using Azure monitoring tools and ServiceNow. Environment: Azure Data Factory | Azure Databricks | PySpark | Delta Lake | ADLS Gen2 | Azure SQL Database | SQL | Python | Power BI | Azure DevOps

Analyst at Virtusa, Mar 2022 - Dec 2023 · 1 yr 10 mos, Gurugram, Worked on designing, developing, and supporting Azure-based data integration solutions for enterprise reporting and analytics platforms. Key Responsibilities & Achievements: • Developed Azure Data Factory pipelines for extracting, transforming, and loading data from multiple source systems into Azure SQL Database. • Created dynamic and reusable ETL workflows using ADF activities including Copy Data, Lookup, ForEach, Conditional Logic, and Stored Procedures. • Implemented incremental data loading frameworks using watermark columns and delta processing techniques to improve pipeline efficiency. • Developed complex SQL queries, stored procedures, and transformation logic for data cleansing, validation, and reconciliation. • Designed optimized datasets for Power BI reporting by creating structured data models and analytics-ready tables. • Automated pipeline scheduling and monitoring using ADF triggers and handled production support activities including incident analysis and resolution. • Collaborated with business analysts and reporting teams to understand requirements and deliver reliable data solutions. Environment: Azure Data Factory | Azure SQL Database | SQL Server | Python | Power BI | Azure DevOps | ServiceNow

Education

PGDM/PGPM, Marketing, unitedworld school of business

Bachelor of Technology, Mechanical Engineering, Lovely Professional University