Data Strategy & Governance Consultant

Role Overview This role owns the enterprise approach to data strategy — analysing the data landscape, shaping consolidation and modernisation strategy, and establishing data governance foundations that form the basis for AI initiatives. Based in the AI CoE, the consultant multiplexes to Data & AI Service Line engagements, advising business and technology stakeholders on how to turn fragmented data estates into AI-ready, governed, and reusable assets. Key responsibilities Data landscape and modernisation strategy Analyse the enterprise data landscape — sources, platforms, pipelines, and architectures — to assess current state and maturity. Define data consolidation and modernisation strategy, including target-state architecture, migration pathways, and platform rationalisation. Assess data readiness for AI use cases; identify and document gaps in availability, quality, completeness and access. Develop the enterprise data roadmap, with value articulation overtime Data Governance Define and maintain data governance standards, policies across the data lifecycle. Establish frameworks for data ownership, quality, lineage, metadata, master data management, privacy, access control, and retention. Set standards for AI-ready data products, pipelines, and reusable data assets in collaboration with enterprise data teams. Advice on responsible and compliant data usage Consult for client engagements Support leadership decision-making through structured recommendations, business cases, and executive briefings. Act as a trusted advisor to stakeholders in client organisations. Facilitate discovery workshops, interviews, and executive alignment sessions; derive actionable recommendations and transformation programs with defined success metrics. Support pre-sales for Service Line Data transformation engagements. Change Management and capability building Define adoption playbooks and change management interventions. Advise on capability-building pathways, collaborating with talent and delivery teams to address skill gaps. Development of consulting assets, accelerators, and Data service offerings. Experience 10–12 years in data strategy, data governance, data architecture, or analytics consulting Expected Skills Demonstrated experience with data platform modernisation, migration strategy, or lakehouse/cloud data architectures Strong grasp of data management concepts — quality, metadata, lineage, ownership, MDM, privacy, and access management Experience defining data governance operating models, maturity models, or data transformation roadmaps Cloud data platforms, enterprise data catalogs, and modern data stack tooling – Hands on experience would be an added advantage. Experience working alongside engineering and architecture teams in a services or product organization Stakeholder skills Excellent executive communication; ability to influence without authority

Educational qualification: B.E/B.Tech/MCA/PhD or equivalent Qualification Experience : 10–12 years in data strategy, data governance, data architecture, or analytics consulting Mandatory/requires Skills : Demonstrated experience with data platform modernisation, migration strategy, or lakehouse/cloud data architectures Strong grasp of data management concepts — quality, metadata, lineage, ownership, MDM, privacy, and access management Experience defining data governance operating models, maturity models, or data transformation roadmaps Cloud data platforms, enterprise data catalogs, and modern data stack tooling – Hands on experience would be an added advantage. Experience working alongside engineering and architecture teams in a services or product organization Preferred Skills :