Description

Detailed Roles and Responsibilities:

Role Objective (Summary)

- Act as the technology and delivery lead for all Data & AI initiatives across the organization.
- Define and implement scalable Data & AI architecture using Microsoft Azure AI and Microsoft Fabric.
- Lead the design, development, and deployment of advanced Machine Learning and AI solutions.
- Drive enterprise data engineering and ETL strategies ensuring high-quality, reliable, and scalable data pipelines.
- Collaborate with business stakeholders to identify AI use cases and translate them into impactful solutions.
- Ensure continuous optimization of models for accuracy, performance, and scalability.
- Establish best practices for AI engineering, MLOps, and AI-DevOps frameworks.
- Govern data and AI standards, ensuring compliance, security, and ethical AI practices.
- Mentor and lead cross-functional teams including data engineers, data scientists, and AI engineers

Responsibilities

Key Responsibilities

Data Engineering & ETL Management

- Design and implement robust data pipelines using Azure ecosystem and Microsoft Fabric.
- Manage ETL processes ensuring data quality, consistency, and availability.
- Optimize data workflows for performance and scalability.

Machine Learning & AI Engineering

- Develop, deploy, and maintain ML models and AI solutions.
- Implement model lifecycle management including training, validation, deployment, and monitoring.
- Drive experimentation and innovation in AI/ML techniques.

Model Optimization & Performance

- Continuously improve model accuracy, efficiency, and reliability.
- Implement performance monitoring and feedback loops.

AI DevOps (MLOps)

- Establish CI/CD pipelines for AI/ML models.




- Implement versioning, monitoring, and governance frameworks for models.

Solution Architecture

- Design end-to-end Data & AI solutions aligned with enterprise architecture.
- Ensure scalability, security, and integration with existing systems.

Stakeholder Management & Leadership

- Collaborate with business, IT, and leadership teams.
- Translate business problems into technical AI solutions.
- Lead and mentor teams, fostering a culture of innovation and excellence.

Reporting Responsibilities:

- Provide regular updates on AI initiatives, model performance, and delivery status.
- Present insights, dashboards, and AI outcomes to leadership.
- Ensure documentation of data pipelines, models, and architecture.
- Drive governance and reporting standards across Data & AI programs.

Qualifications

Key Skills & Competencies

- Strong expertise in Microsoft Azure AI and Microsoft Fabric
- Deep knowledge of Data Engineering, ETL processes, and data architecture
- Experience in Machine Learning, AI modelling, and optimization techniques
- Hands-on experience with MLOps / AI-DevOps frameworks
- Robust problem-solving and analytical skills
- Excellent stakeholder management and communication skills
- Leadership and team management capabilities
- Ability to work in a fast-paced, evolving technology landscape.

Qualifications

- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field

Certifications (Preferred / Added Advantage)

- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Data Engineer Associate
- AI/ML certifications (preferred)
- Certifications in Data Engineering / Cloud Architecture

📌 Head - Data/ AI (India)
🏢 malomatia
📍 India