Data Architect

3 weeks ago

Bengaluru, India Bellfast Management Private Limited Full time

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

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