Responsibilities
- 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.
Requirements
- 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.
- Strong hands-on experience in one of the following technology tracks: 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.
- Hands-on experience designing and deploying AI solutions using Databricks AI capabilities, Vertex AI, foundation models, and enterprise AI frameworks.
- Experience integrating AI capabilities into enterprise data platforms while ensuring governance, security, and responsible AI practices.
- Strong understanding of data quality, lineage, observability, metadata management, and platform governance.
- Excellent stakeholder management, communication, and leadership skills with the ability to bridge business and technology teams.
Nice to Have
- Experience working in Real Estate, Property Technology, Marketplace, Consumer Digital, or adjacent industries is preferred but not required.
