Job Summary

Role Summary

The AI & Data Architect is responsible for defining and governing the enterprise architecture for data, analytics, and AI platforms, ensuring scalable, secure, and compliant AI‑driven solutions. The role bridges business strategy, data platforms, and AI/ML engineering, enabling organizations to turn data into trusted intelligence and measurable business outcomes.

 

Key Responsibilities

Architecture & Strategy

• Define end‑to‑end AI & Data architecture across ingestion, storage, processing, analytics, and AI/ML layers.
• Establish enterprise data and AI architecture standards, patterns, and reference architectures.
• Align AI & Data strategy with business objectives, cloud strategy, and technology roadmaps.

Data Platform & Engineering

• Design modern data platforms (lakehouse, data mesh, data fabric) to support batch, streaming, and real‑time analytics.
• Guide data ingestion, transformation, metadata, lineage, and data quality strategies.
• Ensure interoperability across source systems, analytics platforms, and AI workloads.

AI / ML Enablement

• Architect AI/ML and GenAI solutions including model lifecycle, MLOps/LLMOps, and deployment patterns.
• Support scalable integration of predictive analytics, ML models, and GenAI capabilities into business applications.
• Ensure governable, explainable, and production‑ready AI solutions.

Governance, Security & Compliance

• Embed data governance, privacy, security, and responsible AI principles into architecture designs.
• Ensure compliance with regulatory, risk, and enterprise security standards.
• Define observability, cost optimization, and resilience for AI & data platforms.

Stakeholder Leadership

• Act as a trusted advisor to business leaders, product teams, engineering teams, and vendors.
• Lead architecture reviews, design trade‑offs, and technology selection decisions.
• Mentor teams and promote architectural best practices across programs.

 

Required Skills & Experience

• 10+ years of experience in data, analytics, and architecture roles, with strong AI/ML exposure.
• Deep understanding of:
• Data architectures (Lakehouse, Data Mesh/Fabric)
• AI/ML & GenAI concepts and production patterns
• Cloud platforms (AWS / Azure / GCP)
• Strong experience in enterprise‑scale architecture, system integration, and platform design.
• Ability to translate business vision into scalable technical architectures.

 

Preferred Qualifications

• Experience in regulated industries (Banking, Financial Services, Insurance).
• Exposure to AI governance, model risk, and responsible AI frameworks.

Architecture certifications (TOGAF, Cloud Architect, AI/Data certifications).

Key Responsibilities

1. Architect End-To-End Data Integration And Transformation Solutions Using Azure Data Factory, Ensuring Scalability, Reliability, And Adherence To Enterprise Standards.
2. Design And Oversee Advanced Analytics Platforms Leveraging Azure Databricks, Azure Synapse Analytics, And Azure Ml To Enable Data-Driven Decision-Making.
3. Define And Implement Devops Practices For Data Pipelines In Azure, Ensuring Automated Deployments, Monitoring, And Operational Excellence.
4. Lead Architectural Reviews And Enforce Governance And Compliance Measures Across Azure Data Solutions, Maintaining Alignment With Industry And Organizational Standards.
5. Collaborate With Business Stakeholders To Gather Requirements And Translate Them Into Innovative, Scalable Azure-Based Data Architectures.
6. Mentor And Develop Technical Teams On Azure Data Technologies, Ensuring Skill Advancement And Risk Mitigation In Solution Delivery.
7. Author Whitepapers, Contribute To Industry Forums, And Drive Intellectual Property Initiatives To Establish Thought Leadership In Azure Data Architecture.

Skill Requirements

1. Architectural Leadership In Azure Data Factory With ExpertLevel Proficiency In Designing Complex Data Integration Solutions
2. Advanced Expertise In Azure Databricks, Azure Synapse Analytics, And Azure Ml For LargeScale Analytics And Machine Learning Workloads
3. InDepth Knowledge Of Devops Practices For Azure Data Services, Including Ci/Cd, Monitoring, And Automation
4. Solid Understanding Of Data Governance, Security, And Compliance Frameworks Within Azure Environments
5. Excellent Ability To Translate Business Requirements Into Scalable Azure Data Architectures
6. Strong Mentoring And Leadership Skills To Guide Technical Teams In Azure Data Technologies

Other Requirements

1. Microsoft Certified: Azure Solutions Architect Expert (Recommended)
2. Microsoft Certified: Azure Data Engineer Associate (Optional But Valuable)
3. Microsoft Certified: Azure Data Scientist Associate (Optional But Valuable