Role & responsibilities

- 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

📌 Databricks Architect (Chennai)
🏢 Saaki Argus And Averil Consulting
📍 Chennai