Job Title:  T&T | Engineering | Associate Director | Azure ADF | Gurugram | Data Modernization & Migration

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. 

Your work profile

The manager in Data Strategy, Analytics & AI Innovation, will lead the development and execution of enterprise-wide Data Strategy, Analytics Strategy, and AI transformation initiatives. The role will be responsible for establishing modern data platforms, enabling advanced analytics, driving AI/ML adoption, and building organizational capabilities to accelerate digital transformation across Manufacturing, Supply Chain, Sales, After-Sales, Dealer Network, and Corporate Functions.

Key Skills & Competencies

• Act as a subject matter expert in Data Strategy, Analytics, Artificial Intelligence, Machine Learning, and Generative AI.
• Provide strategic and technical leadership to define and execute enterprise data and AI initiatives.
• Establish best practices, solution architectures, governance frameworks, and implementation standards.
• Advise leadership on data, analytics, and AI investments, platform strategy, technology selection, and innovation roadmaps.
• Evaluate emerging technologies and identify opportunities to create business value through data and AI.

• Define and execute the enterprise Data & AI capability development roadmap.
• Design and drive structured learning programs covering:
• Data Engineering
• Data Science & Advanced Analytics
• Artificial Intelligence & Machine Learning
• Generative AI
• Data Governance & Data Management
• Cloud Data Platforms and Modern Analytics
• Assess current capabilities, identify skill gaps, and recommend targeted training, certifications, mentoring, and hands-on implementation programs.
• Develop internal competencies and reusable assets to enable sustainable, scalable delivery of Data & AI initiatives.

• Partner closely with business and technology stakeholders to identify high-value opportunities for analytics, automation, and AI-driven transformation.
• Translate business challenges into data-driven solutions that deliver measurable business outcomes.
• Facilitate the identification, prioritization, and implementation of Data, Analytics, and AI use cases.
• Support organizational adoption and change management for data-driven decision-making and AI-powered business processes.
• Serve as a liaison between business, IT, data, and AI teams to ensure alignment and successful delivery.

• Define and maintain the enterprise Data & AI Strategy aligned to business objectives and digital transformation priorities.
• Develop a multi-year roadmap for data modernization, analytics adoption, and AI implementation.
• Establish governance frameworks covering data management, data quality, security, privacy, Responsible AI, and MLOps.
• Drive the creation of enterprise data products, semantic layers, and analytics frameworks to support decision intelligence.
• Promote enterprise-wide adoption of data-driven culture and AI-led innovation.

• Lead the architecture, implementation, and scaling of enterprise Data, Analytics, and AI platforms leveraging:
• Microsoft Azure
• Azure Data Factory (ADF)
• Microsoft Fabric
• Azure Synapse Analytics
• Azure Databricks
• Azure Data Lake Storage (ADLS)
• Azure AI Services
• Azure OpenAI Service
• Azure Machine Learning
• Azure Cognitive Services
• Microsoft Power BI
• Microsoft Purview
• Design and implement modern data platforms, enterprise data lakes, data warehouses, and analytics ecosystems.
• Build scalable and reusable data pipelines, semantic models, feature stores, AI accelerators, and model management frameworks.
• Establish enterprise-wide DataOps and MLOps practices covering deployment, monitoring, retraining, observability, governance, and security.
• Implement metadata management, data lineage, data quality, master data management, and governance controls.
• Enable self-service analytics, reporting, and business intelligence capabilities through governed data products and semantic models.
• Drive platform optimization, scalability, performance, security, and cost management across the data and AI ecosystem.
• Develop reference architectures and standards for Data Engineering, Analytics Engineering, AI/ML Engineering, and Generative AI implementations.

• Provide strategic oversight and guidance for Data, Analytics, and AI programs and projects.
• Review solution designs, implementation approaches, and program deliverables to ensure alignment with enterprise standards.
• Monitor progress, risks, dependencies, and value realization across the Data & AI portfolio.
• Support executive reporting and stakeholder communication on transformation progress and outcomes.

Preferred Qualifications

• Education - B. tech / BE in Computer Science or Information Technology.

Location and way of working:

• Base location: Delhi NCR
• This profile involves travelling to client locations