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Bosch Global Software Technologies Private Limited in Bengaluru is seeking a senior consultant to lead enterprise data strategy and governance initiatives. You will analyse the data landscape, define consolidation and modernisation roadmaps, and establish governance foundations to enable AI-ready, governed, and reusable data assets across the enterprise.
The role sits in the AI CoE and collaborates with Data & AI Service Line engagements, advising stakeholders and shaping transformation programs
Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development centre of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.
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.
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
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
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.
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.
10–12 years in data strategy, data governance, data architecture, or analytics consulting
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
Excellent executive communication; ability to influence without authority
B.E/B.Tech/MCA/PhD or equivalent Qualification
10–12 years in data strategy, data governance, data architecture, or analytics consulting
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