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Navin Shah
@navin_shah
Data Engineer Data Architect Azure Databricks Microsoft Fabric
Inde
Anglais
À propos de moi
Data Engineer and Data Architect with 10+ years of experience working with global technology companies. I specialize in Azure, Databricks, Microsoft Fabric, PySpark, Python, SQL, Spark, Delta Lake, OneLake and Power BI. I build scalable ETL/ELT pipelines, lakehouse and data warehouse solutions, data models, and analytics platforms. I also help troubleshoot and optimize data pipelines, improve performance, and implement data quality, security and governance.
Compétences
Navin Shah
hors ligne •
Temps de réponse moyen de 1 heure
Voir mes services
Conseil en ingénierie des données
I will build microsoft fabric data pipelines and lake house solutions
Portfolio
Expérience professionnelle
Senior Data Engineer
KGroup Global Services • Temps plein
May 2026 - Sep 2026 • 4 mos
• Design Lakehouse architecture based on Medallion architecture on MS Fabric • Migrate legacy system to Lakehouse architecture • Designed and implemented automation workflows and Azure services including Azure Data Factory and data bricks on Fabric • Monitor data pipelines, troubleshoot issues and implement optimization for performance and reliability. • Built and monitored interactive dashboards and reporting solutions using Power BI, integrating with Fabric and Databricks for real-time data insights as part of the data engineering ecosystem. • Automated business processes and optimized database integration using Python, Apache Spark, Databricks, and cloud-based ETL pipelines. Delivered scalable analytics solutions across hybrid environments, supporting advanced data modeling and performance tuning. • Manage and Lead team to meet SLA and work flows. • Monitor and support job failure for different jobs running across different platform like Talend, Databricks, Fabric, SSIS, ADF.
Technical Lead
Coforge • Temps plein
Jul 2025 - May 2026 • 10 mos
• Develop, test, and deploy data ingestion, transformation and processing using Azure services • like Azure Data Factory, Azure Data Lake Storage, Talend, Microsoft Fabric based on medallion architecture • Designed and implemented automation workflows and Azure services including Azure Data Factory and Fabric Powe BI • Monitor data pipelines, troubleshoot issues and implement optimization for performance and reliability. • Built and monitored interactive dashboards and reporting solutions using Power BI, integrating with Azure and Databricks for real-time data insights as part of the data engineering ecosystem. • Automated business processes and optimized database integration using Python, Apache Spark, Databricks, and cloud-based ETL pipelines. Delivered scalable analytics solutions across hybrid environments, supporting advanced data modeling and performance tuning. • Manage and Lead team to meet SLA and work flows. • Monitor and support job failure for different jobs running across different platform like Talend, Databricks, Fabric, SSIS, ADF.
Senior Data Engineer
Resurgent Enterprise Solutions • Temps plein
Dec 2023 - May 2025 • 1 yr 5 mos
• Develop, test, and deploy data ingestion, transformation and processing using Azure services • like Azure Data Factory, Azure Data Lake Storage, Microsoft Fabric • Designed and implemented medallion architecture ,automation workflows and Azure services including Azure Data Factory • Monitor data pipelines, troubleshoot issues and implement optimization for performance and reliability. • Built and monitored interactive dashboards and reporting solutions using Power BI, integrating with Azure and Databricks for real-time data insights as part of the data engineering ecosystem. • Automated business processes and optimized database integration using Python, Apache Spark, Databricks, and cloud-based ETL pipelines. Delivered scalable analytics solutions across hybrid environments, supporting advanced data modeling and performance tuning. • Data transformation using PySpark and python for ETL/ELT pipeline. • Develop CI/CD along with SCD I/II with GitHub action for streaming data.
