Role Description

Key Responsibilities

- Design and architect enterprise-scale Databricks Lakehouse solutions aligned with business, analytics, AI, and data modernization objectives.
- Define scalable and secure data platform architectures leveraging Delta Lake, Unity Catalog, Medallion Architecture, and Databricks Workflows.
- Architect cloud-native data solutions on Azure and AWS, integrating services such as ADLS, Azure Event Hubs, Azure Data Factory, Amazon S3, MSK/Kafka, IAM, and cloud-native security frameworks.
- Design batch and real-time data processing solutions using Auto Loader, Delta Live Tables (DLT), Structured Streaming, Kafka, and Event Hubs.
- Establish enterprise data governance, security, lineage, privacy, and compliance frameworks utilizing Unity Catalog, fine-grained access controls, and audit capabilities.
- Lead the architecture and implementation of GenAI, Agentic AI, RAG, Mosaic AI, Vector Search, MLflow, and Databricks Genie solutions.
- Define MLOps, AI governance, and model lifecycle management strategies covering explainability, observability, risk management, and regulatory compliance.




- Drive cloud modernization and migration initiatives from legacy and on-premise platforms to Databricks-based lakehouse architectures.
- Establish DataOps, CI/CD, Infrastructure as Code (Terraform), and platform automation standards for enterprise-scale deployments.
- Optimize platform performance, scalability, resilience, and cost efficiency through architecture best practices, workload management, and FinOps principles.
- Conduct architecture reviews, define enterprise standards, assess technical risks, and ensure alignment with organizational governance frameworks.
- Provide technical leadership, stakeholder engagement, executive-level advisory, solution roadmap definition, and mentoring to engineering and architecture teams.
- Key Skills / Technologies
- Databricks: Delta Lake, Unity Catalog, DLT, Auto Loader, Databricks Workflows, Delta Sharing, Lakehouse Monitoring, Databricks Genie, Mosaic AI, MLflow, Vector Search
- Cloud: Azure (ADLS, Event Hubs, ADF, Key Vault, Azure DevOps), AWS (S3, IAM, Glue, MSK, Lambda, CloudWatch)
- AI/GenAI: RAG, AI Agents, LLMs, Vector Search, Prompt Engineering, Model Governance
- DevOps: Terraform, CI/CD, DataOps, GitHub Actions, Azure DevOps

Skills

Databricks, AWS, Azure DevOps

📌 Data Architect I (Pune)
🏢 UST
📍 Pune