Infosys Consulting is seeking an experienced Data Management Consulting Specialist with deep domain knowledge across Data for AI, Semantic Metagraphs, Ontologies, Data Quality, and Data Governance — combined with the commercial capability to shape and sell data management offerings to enterprise clients. This is a consulting role: the individual must be technically fluent enough to lead credible conversations with client data architects and engineering teams, but is not expected to be a hands-on data engineer or developer.
The candidate must have a background as a Data Architect or Data Advisor in a consulting context, direct engagement experience with Chief Data Officers (CDO) and Chief AI Officers (CAIO), and a track record in pseudo-sales / pre-sales within Tier 1 IT firms, Big 4, or consulting organizations. Total experience of 14+ years is required, with at least 8 years specifically in data management, data architecture, or data governance consulting.
Responsibilities:
Key responsibilities include:
- Data Advisory & Strategy: Advise clients on data strategy, data architecture approach, and data platform direction — framing how data assets need to be structured and governed to enable AI and analytics at scale.
- Pseudo-Sales & Pre-Sales: Lead and actively participate in data management offering pitches, RFP responses, client discovery workshops, and solution shaping for data transformation and data for-AI deals.
- C-Suite Stakeholder Engagement: Engage directly with Chief Data Officers (CDO), Chief AI Officers (CAIO), and senior business stakeholders — articulating data strategy value, governance maturity, and the data-AI connection at the executive level.
- Semantic & Ontology Advisory: Advise clients on semantic metagraph models, ontology design, and metadata management — able to explain concepts clearly and validate approaches with client teams without building them personally.
- Data Governance & Quality Advisory: Define and advise on data governance frameworks, data quality strategies, MDM approaches, and data lineage — leveraging knowledge of tools like Collibra, Alation, Microsoft Purview, Informatica IDMC, and Ataccama.
- Data for AI Consulting: Shape client thinking on what data foundations are required for AI/ML — including data readiness, feature engineering considerations, vector store strategy, and synthetic data concepts.
- Data Offerings Development: Develop and articulate reusable data management consulting offerings, practice frameworks, and go-to-market assets.
- Regulatory & Compliance Awareness: Guide clients on data compliance obligations (GDPR, HIPAA, 21 CFR Part 11) relevant to data governance in regulated industries.
- Thought Leadership: Contribute to data strategy frameworks, POV documents, white papers, and internal data communities of practice.
- Billability & Practice Growth: Expected to maintain 65%–75% billability annually through active client engagements, while dedicating the remaining time to practice development activities — including offering creation, RFP pursuit, thought leadership, and capability building.
Mandatory Skills:
- Data Architecture Awareness (Consulting): Strong conceptual and advisory knowledge of enterprise data architectures — data lakes, lakehouses, data mesh, semantic layers — sufficient to lead client conversations, validate delivery approaches, and shape engagements; not hands-on implementation
- Data for AI: Deep understanding of what data foundations are needed for AI/ML — including data readiness, feature engineering concepts, vector stores, embedding strategies, and synthetic data — able to advise CAIOs and CDOs on data-AI readiness
- Semantic Metagraph & Knowledge Graphs: Strong conceptual knowledge of semantic metagraph models, enterprise ontologies, and knowledge graph design (RDF/OWL, SPARQL, Neo4j or similar); able to advise clients and validate designs without personally building them
- Ontology & Metadata Management: Ability to explain, advise on, and review business and technical ontologies; familiarity with metadata standards (DCAT, Dublin Core, FIBO, BioPortal) in a client advisory context
- Data Quality Advisory: Strong knowledge of data quality frameworks, profiling strategies, and remediation approaches; experienced in advising clients on tooling (Ataccama, Informatica DQ, Great Expectations, Talend) and governance models
- Data Governance Tools & Platforms: Demonstrated advisory experience with at least one enterprise data governance platform: Collibra, Alation, Microsoft Purview, Informatica IDMC, or Ataccama; able to advise on selection, operating model, and implementation approach
- Pre-Sales / Pseudo-Sales: Minimum 3 years of active data-focused pre-sales / pseudo-sales experience: RFPs, client pitches, discovery workshops, and data transformation proposals — within the last 8 years of their data career
- C-Suite Stakeholder Engagement: Demonstrated experience engaging directly with Chief Data Officers (CDO), Chief AI Officers (CAIO), or equivalent senior client executives; able to hold strategic data advisory conversations at the executive level
- Consulting Background & Experience: 14+ years total experience, with at least 8 years in data management, data architecture, or data governance consulting at a Tier 1 IT firm (TCS, Wipro, Cognizant, Infosys, Accenture, Capgemini) or Big 4 / consulting firm
- Data Governance Frameworks: Strong knowledge of DAMA-DMBOK, DCAM, or equivalent data management maturity frameworks; able to assess client maturity and recommend a governance roadmap
Basic Qualification:
Demonstrates proven success in roles and thorough abilities in one or more of the following areas:
- Education: Bachelor's or Master's degree in Computer Science, Information Management, Data Engineering, Business, or related field
- Total Experience:14+ years, with at least 8 years in data management, data architecture, or data governance consulting
- Previous Employers: TCS, Wipro, Cognizant, Infosys, Accenture, Capgemini, HCLTech, Deloitte, EY, KPMG, PwC, or equivalent Tier 1 / Big 4 / consulting organizations
Desired Skills:
- Master Data Management (MDM) Advisory: Knowledge of MDM platforms (Informatica MDM, Reltio, Profisee, SAP MDG) and ability to advise clients on MDM strategy and operating model
- Cloud Data Platforms Awareness: Familiarity with Snowflake, Databricks, Azure Synapse, Google BigQuery, or AWS Redshift — able to discuss platform trade-offs and architecture patterns with client teams
- Data Lineage & Observability: Awareness of data lineage tools (OpenLineage, Atlan) and data observability platforms (Monte Carlo, Acceldata); able to advise clients on lineage strategy
- AI-Ready Data Products: Knowledge of data product design in the context of data mesh or data marketplace; able to advise clients on data product strategy for AI consumption
- Regulatory Data Compliance: Familiarity with GDPR, HIPAA, CCPA, 21 CFR Part 11, or industry specific data regulations — particularly in Life Sciences or Pharma
- Domain Knowledge: Experience in regulated industries — Life Sciences, Pharma, BFSI, or Healthcare — where data integrity, lineage, and governance carry regulatory weight
- Data Modelling Awareness: Familiarity with conceptual, logical, and physical data modelling concepts; able to review models and advise on modelling standards using tools such as SQLDBM, erwin, or PowerDesigner
- Graph Databases: Conceptual awareness of Neo4j, Amazon Neptune, or TigerGraph for enterprise knowledge graph use cases — able to advise on applicability
- Certifications: CDMP (DAMA), Collibra Certified Data Citizen/Engineer, Informatica Data Quality Specialist, or equivalent
- Thought Leadership: Authored frameworks, white papers, or conference contributions on data governance, semantic data modelling, data mesh, or data strategy
