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Data Engineer with 5+ years in Azure Data Platforms & ETL
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Azure Data Engineer with 5+ years of experience designing and implementing enterprise-scale data platforms on Azure. Expertise in Azure Data Factory, Azure Databricks, PySpark, Delta Lake, and ADLS Gen2 for building scalable batch and real-time data processing solutions. Experienced in Medallion Architecture, CDC frameworks, Structured Streaming, metadata-driven ETL pipelines, Spark performance optimization, and Azure DevOps CI/CD. Strong background in Lakehouse architecture, data governance, monitoring, production support, and performance tuning for enterprise data workloads.
Gurgaon College of Engineering
B.Tech
May 1, 2011 – May 1, 2015
UCSKM PUBLIC SCHOOL
12th
April 1, 2010 – March 1, 2011
REPRO INDIA LTD
AZURE DATA ENGINEER
March 1, 2023 – Present
Dhāruhera, Haryana, India
SHREE HARI WIRES
DATA ENGINEER
September 1, 2020 – February 1, 2023
Bhiwadi, Rajasthan, India
Real-Time Lakehouse Pipeline using Azure Data Factory and Azure Databricks
June 22, 2026 – Present
Designed and implemented an end-to-end Lakehouse solution using Azure Data Factory, Azure Databricks, Delta Lake, and ADLS Gen2. Developed metadata-driven ingestion framework using control tables for dynamic pipeline execution. Implemented parent-child pipeline architecture using Execute Pipeline activity and dynamic parameter passing. Built Bronze, Silver, and Gold layers using Medallion Architecture for scalable and reliable data processing. Implemented CDC pipelines using Delta MERGE for handling insert, update, and delete operations. Developed Structured Streaming pipelines for near real-time ingestion from Kafka/Event Hub into Delta tables. Applied data quality checks, schema validation, deduplication, watermarking, and audit logging frameworks. Optimized Spark workloads using partitioning, broadcast joins, caching, AQE, OPTIMIZE, VACUUM, and ZORDER. Implemented monitoring and alerting framework using Azure Monitor, Logic Apps, and Web Activities. Automated deployments across DEV, UAT, and PROD environments using Azure DevOps CI/CD pipelines. Used Unity Catalog for data governance, access control, and secure data management. Developed reusable ETL workflows and parameterized frameworks to improve maintainability, scalability, and operational efficiency of data integration processes.
The candidate scored 80% on the 'Data Engineer — Azure (Databricks DLT / Streaming / Cost)' test, indicating a solid understanding of core Azure data engineering concepts, particularly around Databricks, Delta Lake, and streaming, which are critical for the target role.
Strengths
Limitations
Cultural Fit Analysis
The candidate's experience across two companies, with diverse projects involving various Azure data services and methodologies (e.g., metadata-driven frameworks, real-time pipelines, CI/CD), suggests adaptability and a broad skill set. The focus on enterprise-scale data platforms and collaboration in Agile environments indicates a good fit for a dynamic, team-oriented culture. The psychometric test score, however, warrants further investigation into specific areas like stress handling or team collaboration to ensure a complete cultural alignment.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with business stakeholders and cross-functional teams in Agile/Scrum environments, indicating good team collaboration and communication skills. Experience in troubleshooting production incidents and implementing performance improvements demonstrates problem-solving and operational reliability. The psychometric test score of 257/500 suggests potential areas for development in logical reasoning, work attitude, or stress handling, which could impact operational fit.