Data Strategy & Governance Consultant
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What you'll do
- 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.
What they're looking for
- 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Company Description
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 center 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.
Job Description
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
Qualifications
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 :
Company
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