Shreedhar Tupe

Data Engineer with 3.8+ years of experience designing scalable, cloud-native data platforms and delivering end-to-end data solutions on Microsoft Azure. Proven expertise in building high-performance ETL pipelines using Azure Data Factory, Synapse Analytics, and Databricks, with measurable impact including 30% reduction in data latency, 20% cost optimization, and improved analytics delivery. Strong experience in cloud migrations, data modeling, and real-time processing, with the ability to collaborate across cross-functional teams to deliver business-driven data solutions.

Associate Consultant at Capgemini (2025-04 – Present)

Data Engineer building scalable Azure data pipelines and cloud migration solutions

• Resulted in improved data accessibility, faster analytics, and reduced infrastructure dependency
• Designed and delivered scalable Azure data pipelines (ADF + Synapse) supporting large-scale cloud migration initiatives
• Built automated workflows using Azure Functions and Logic Apps, improving data processing efficiency and reducing manual effort
• Optimized reporting pipelines, achieving ~30% reduction in data latency and improved data accuracy across systems
• Collaborated with cross-functional teams to deliver business-critical data solutions for analytics and reporting
• Optimized Spark jobs using partitioning and caching techniques, improving performance by 22%

Sr. Analyst at Capgemini (2024-04 – 2025-03)

Led cloud migration projects and architected scalable data solutions

• Led end-to-end cloud migration projects, transitioning on-prem data systems to Azure with 100% data accuracy
• Architected scalable data solutions using ADF, Synapse, and Databricks, improving pipeline performance by 25%
• Enabled real-time analytics use cases using Databricks and event-driven workflows
• Optimized cloud resource utilization, achieving ~20% cost savings
• Designed and implemented star schema and SCD Type 2 models for analytics use cases

Analyst at Capgemini (2022-08 – 2024-03)

Developed ETL pipelines and automated internal systems

• Developed and maintained ETL pipelines and data workflows using Azure Synapse and SQL
• Automated internal systems (employee ranking, interview tracking), improving operational efficiency by 15–30%
• Built self-healing automation frameworks, reducing manual intervention by 60%
• Designed serverless workflows using Azure Functions for business process automation, reducing turnaround time by 50%

Bachelor of Engineering in Electronics Engineering – Pillai College of Engineering, New Panvel (2018-07 – 2022-07)