Jeeva Kumaresan
Lead Data Engineer (Client Mb Energy) @Publicis Sapient
Signup · Get unlimited contacts
WORK HISTORY
Lead Data Engineer (Client Mb Energy) @Publicis Sapient
GB
I work as a Lead / Senior Data Engineer, designing and delivering data and analytics solutions for the energy sector, with a strong focus on Databricks-based Lakehouse architectures. My work includes developing scalable data pipelines using Azure Data Factory (ADF) and Databricks, with Unity Catalog for data governance and access control.My role spans platform design, implementation, and modernization of large-scale enterprise data systems, enabling scalable, reliable, and cost-efficient data platforms.Key Initiatives and ImpactLed integration of multiple third-party vendor systems by analysing API specifications, validating endpoints using Postman, and implementing scalable ingestion pipelines using Azure Data Factory (ADF).Built parameterized data ingestion frameworks using Azure Data Factory and Databricks, accelerating onboarding of new data sources and improving pipeline reusability.Optimized Databricks workloads and cluster configurations, significantly reducing compute costs and improving pipeline performance.Implemented CI/CD automation using Databricks Resource Bundles, enabling reliable and repeatable platform deployments.Designed and developed scalable data ingestion and transformation pipelines supporting enterprise analytics and reporting workloads.Led data architecture and platform design for a major ERP migration program covering 100+ entities, enabling standardized enterprise data models and reporting across the organisation.
EDUCATION
Delhi University
Bachelor of Science (BSc), Physics
Guru Gobind Singh Indraprastha University
Master of Computer Applications (MCA), Computer Programming
ABOUT JEEVA KUMARESAN
Lead Data Engineer with 16+ years of experience building scalable cloud data platforms on Azure and GCP for the Banking, Financial Services, and Energy sectors. Expert in Spark/PySpark, Scala, Python, SQL, and Kafka, with deep experience in both batch and real-time streaming architectures, delivering resilient, high-volume data pipelines and reusable engineering frameworks. Experienced in Data Mesh and Medallion architectures, CI/CD automation, and cloud-native engineering practices that improve reliability and reduce operational complexity. Driving AI enablement of enterprise data platforms through RAG, vector search, and agentic workflows to power intelligent data products. Proven technical leader in architecting distributed systems and mentoring engineering teams.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.