We are seeking an experienced and strategic Data Strategy Consultant with 13 - 15 years of experience to define, shape, and drive enterprise - wide data transformation initiatives. The successful candidate will bring deep expertise in data strategy, enterprise data architecture, modern data platforms, cloud transformation, business intelligence, and AI - driven business solutions.

This role will serve as a strategic bridge between business leadership, data and enterprise architects, technology teams, and engineering organizations, translating business priorities into scalable, secure, and sustainable data and AI capabilities.

The ideal candidate should have strong experience designing and implementing modern data ecosystems, particularly within the Microsoft technology ecosystem, and should be comfortable engaging with C - level stakeholders while providing architectural direction to engineering teams.

Experience:

- 13 - 15 years of overall experience in data, analytics, technology consulting, enterprise architecture, or related fields.

- Proven experience leading enterprise data strategy and transformation programs.

- Strong hands - on and strategic understanding of modern data platforms, cloud architecture, data integration, analytics, and AI.

- Experience working with large, complex organizations and cross - functional technology teams.

- Demonstrated experience engaging with senior business and technology stakeholders, including C - level executives.

Key Responsibilities:

1. Enterprise Data Strategy:

- Define and drive enterprise - wide data strategies aligned with business objectives, technology roadmaps, and organizational priorities.

- Assess current - state data landscapes, identify gaps, and develop target - state data strategies and transformation roadmaps.

- Establish principles, standards, frameworks, and governance models for enterprise data management.

- Define strategies for data modernization, data democratization, analytics enablement, and AI adoption.

- Develop business cases and value propositions for strategic data and AI investments.

- Identify opportunities to improve data quality, accessibility, interoperability, security, and usability across the enterprise.

- Define measurable outcomes and KPIs to track the business value and maturity of data transformation initiatives.

2. Enterprise Data Architecture:

- Define and govern enterprise data architecture across on - premise, cloud, and hybrid environments.

- Design scalable and future - ready architectures covering data ingestion, integration, storage, processing, governance, analytics, and AI.

- Develop reference architectures, architecture patterns, technology standards, and solution blueprints.

- Evaluate existing data platforms and recommend modernization or consolidation strategies where appropriate.

- Ensure architectural decisions support scalability, security, performance, resilience, cost optimization, and regulatory requirements.

- Collaborate with enterprise, solution, security, and infrastructure architects to ensure alignment with broader technology architecture.

3. Microsoft Data & AI Ecosystem:

- Design and guide modern data and AI architectures leveraging the Microsoft ecosystem, including:

1. Microsoft Fabric - OneLake, Data Factory, Lakehouse, Warehouse, Real - Time Intelligence, and related capabilities.

2. Azure AI - AI services, machine learning, generative AI, and intelligent application capabilities.