Databricks Architect - R01568474

12-15 years of experience in Data Architecture, Data Engineering, Cloud Data Platforms, and AI/GenAI solutions, with proven experience designing and delivering enterprise-scale data and AI platforms.

We are seeking a Data & AI Architect to lead the design and implementation of modern data and AI platforms.

The ideal candidate will bring deep expertise in either the Databricks ecosystem or Google Cloud Platform (GCP), combined with strong data engineering and architecture fundamentals and hands-on experience with Generative AI and Agentic AI solutions.

The role will be responsible for defining scalable data architectures, enabling AI adoption, and driving modernization initiatives across data, analytics, and AI capabilities.

• Lead the architecture and design of enterprise Data & AI platforms supporting analytics, reporting, machine learning, and AI-driven business capabilities.
• Define scalable data architecture, governance, security, and operational frameworks for modern cloud-native platforms.
• Partner with business and technology stakeholders to identify and prioritize data modernization, AI, and automation opportunities.
• Architect and guide implementation of AI, Generative AI, and Agentic AI solutions leveraging enterprise data assets.
• Establish architecture standards, best practices, and technology roadmaps across data engineering and AI initiatives.
• Provide technical leadership and mentorship to engineering, platform, and AI teams.
• Strong expertise in data architecture, data engineering, data warehousing, data lakes, lakehouse architectures, data modeling, metadata management, and data governance.
• Proven experience designing and implementing enterprise-scale data platforms from ingestion through analytics and AI consumption layers.
• Deep understanding of batch, streaming, and real-time data processing architectures.
• Strong hands-on experience in one of the following technology tracks:
• Databricks Track: Databricks Lakehouse Platform, Delta Lake, Unity Catalog, Spark, Workflows, ML/AI capabilities, Mosaic AI, Agent frameworks, and enterprise data engineering patterns.
• Google Cloud Track: BigQuery, Dataproc, Dataflow, Vertex AI, Cloud Storage, AI/ML services, and modern cloud-native data platform architectures.
• Experience building scalable cloud-native data platforms with strong focus on performance, governance, security, and operational excellence.
• Strong understanding of Generative AI, LLMs, RAG, Vector Databases, AI Agents, Multi-Agent Architectures, and Agentic AI patterns.