Job Summary
We are looking for a Data Architect with strong experience in Databricks, enterprise data modernization, and AI-led development to help clients establish a Databricks Data Intelligence Platform that unifies data, governance, analytics, and intelligent application enablement. In this role, you will lead scalable cloud data architecture, modernize legacy environments, embed intelligence into platform engineering, establish governance standards, and build trusted foundations for advanced analytics and intelligent data products.
Key Responsibilities
1. To assess the domain IT landscape assessment and Application portfolio optimization for gap analysis
2. Creation of solution and architectural views (logical| conceptual| development| execution| infrastructure & operations architecture)
3. To collaborate with business and technical stakeholders, including leaders, project managers, and development teams, to understand and prioritize requirements while defining the architecture.
4. To ensure knowledge up-gradation and work with new and emerging products/technologies
5. To drive innovation by exploring and recommending new solutions within the organization.
6. To contribute towards white/technical papers and knowledge base
Skill Requirements
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 10+ years of experience in data architecture, data engineering, or enterprise data platform design.
• Hands-on expertise in Databricks, Spark/PySpark, SQL, Python, PyTorch, and cloud data platforms.
• Strong experience in data modernization, migration, governance, performance optimization, and enterprise architecture for client-facing delivery.
• Proven experience enabling AI-driven development, ML workflows, and model lifecycle management, including production implementations with security guardrails and evaluation/review frameworks.
• Excellent stakeholder communication and cross-functional leadership skills.
Other Requirements
• Master’s degree or advanced certification in data, cloud, AI, or intelligent platform engineering disciplines.
• Experience with Azure Databricks and one or more major cloud platforms (AWS or GCP).
• Knowledge of vector databases, intelligent application patterns, platform governance, and frameworks for guardrails, response quality evaluation, and human review.
• Experience with CI/CD, Infrastructure as Code, observability, and DataOps/MLOps practices.