Architect and implement enterprise-grade Lakehouse solutions using Databricks
Design and deliver scalable batch and real-time data pipelines using Apache Spark (PySpark/SQL)
Build ETL/ELT pipelines, incremental data loads, and metadata-driven ingestion frameworks
Implement and optimize Databricks components: Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, and Workflows
Design large-scale data warehousing solutions with 3NF and dimensional modeling
Establish data governance, security, and data quality frameworks, including Unity Catalog
Lead ML lifecycle management using MLflow and drive AI use cases (RAG, AI/BI)
Manage cloud-native deployments on Microsoft Azure and integrate with enterprise systems (e.g., ServiceNow)
Drive CI/CD, DevOps practices, and performance optimization of Spark workloads
Provide technical leadership, mentor teams, and ensure successful delivery
Collaborate with stakeholders to translate business requirements into scalable solutions