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Data Architect - Databricks

Posted on: 29/09/2025

Job Description

Key Responsibilities :


Solution 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 outcomes.

Databricks & 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 Databricks.


- 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).

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