Data Architect - Databricks

<p><p><b>Key Responsibilities Architecture & Design :</b></p><p><p><b><br/></b></p><p>- Define best practices for data pipelines, orchestration, and governance using Lakehouse architecture.<br/><p><br/></p><p>- Partner with product, business, and engineering teams to align architecture with business & AI Expertise : </b></p>- Hands-on implementation and optimization of Databricks AI tools, including :<ul><li>Agent Bricks (AI agent orchestration)</li></ul><ul><li>Lakeflow Designer (data workflow automation)</li></ul><ul><li>MLflow (ML lifecycle management)</li></ul><ul><li>Genie or Mosaic AI (generative AI & enterprise search)</li></ul>- At least one end-to-end implementation experience of AI/ML workloads using Architect large-scale data platforms leveraging Databricks for advanced analytics, AI/ML, and real-time data processing.<br/></p><p><br/></p>- Stay updated with the latest industry trends in AI, MLOps, LLMOps, and data architectures.<br/><br/><b>Leadership & Stakeholder Engagement : </b><br/><p><br/></p><p>- Lead technical discussions and workshops with cross-functional stakeholders across global geographies.</p><br/>- Provide technical thought leadership and mentor junior engineers/architects.<br/><br/>- Collaborate with enterprise architects, data scientists, and cloud engineers to ensure architectural consistency.<br/><br/><b>Innovation & Best Practices : </b><br/><br/><p><br/></p><p>- Establish architectural blueprints, standards, and data governance practices.</p><br/>- Evaluate new tools, frameworks, and methodologies for adoption in the data ecosystem.<br/><br/>- Drive performance tuning, cost optimization, and scalability in Databricks and AI solutions.<br/><br/><b>Must-Have Skills : </b><br/><br/><p><br/></p><p>- 10+ years in data engineering/architecture, with strong hands-on experience in Databricks.</p><br/>- Expertise in Databricks AI suite (Agent Bricks, Lakeflow Designer, MLflow, Genie or Mosaic AI).<br/><br/>- Proven end-to-end AI/ML implementation experience on Databricks.<br/><br/>- Strong knowledge of Delta Lake, PySpark, SQL, and Data Lakehouse design patterns.<br/><br/>- Excellent understanding of MLOps / LLMOps, model deployment, and monitoring.<br/><br/>- Strong communication and stakeholder management skills with global exposure.<br/><br/><b>Good-to-Have Skills : </b><br/><br/><p><br/></p><p>- Cloud platform experience (Azure, AWS, or GCP) with Databricks.</p><br/>- Exposure to GenAI, Vector Databases, RAG frameworks.<br/><br/>- Familiarity with data security, compliance, and privacy regulations.<br/><br/>- Industry certifications (e.g., Databricks Certified Data Architect / ML Professional).<br/><br/></p> (ref:hirist.tech)