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About Brillio :
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio , renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio 's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Databricks Architect
Experience
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.
Role Overview
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.
Key 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.
Required Skills & Experience
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.
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.
Experience working in Real Estate, Property Technology, Marketplace, Consumer Digital, or adjacent industries is preferred but not required."
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