Sr. Data Architect

Requirements:

• Bachelor's or Master's degree in Computer Science, Information Technology, Information Systems, or a related engineering discipline.
• 10-15 years of progressive experience in data architecture, data engineering, or enterprise information management roles - with at least 5 years in a senior architect capacity.
• Demonstrable, hands-on experience working with large MNC data estates encompassing legacy systems and one or more major ERP platforms: SAP (S/4HANA, ECC, BW), Oracle EBS/Fusion, or Microsoft Dynamics 365
• Deep expertise in data modelling - conceptual, logical, and physical - including dimensional modeling, data vault, and normalized relational models for both OLTP and OLAP use cases.
• Proven experience designing data ontologies, taxonomies, and business glossaries using formal standards (RDF, RDFS, OWL) and ontology tooling such as Protg.
• Strong proficiency in SQL and at least one programming or scripting language (Python, Scala, or equivalent) for data discovery, profiling, and architecture validation.
• Hands-on experience with at least one major cloud data platform - AWS (Redshift, Glue, Lake Formation, S3), GCP (BigQuery, Dataplex, Dataflow), or Azure (Synapse Analytics, Purview, ADLS).
• Experience designing and implementing MDM frameworks and familiarity with at least one MDM platform (Informatica MDM, SAP MDG, IBM MDM, or equivalent).

Good to Have:

• Experience with knowledge graph platforms and graph databases - Neo4j, Amazon Neptune, or Azure Cosmos DB (Gremlin API).
• Familiarity with enterprise architecture frameworks such as TOGAF, Zachman, or equivalents.
• Exposure to data mesh architecture principles and federated data ownership models.
• Knowledge of AI/ML data platform requirements - feature stores, vector databases, training data management - and how they integrate with enterprise data architectures.
• Experience with data fabric platforms such as Informatica IDMC, Talend, or IBM Cloud Pak for Data.
• Familiarity with data observability and data quality tools - Collibra, Alation, Monte Carlo, Great Expectations, or Soda.
• Understanding of data privacy regulations relevant to MNC operations - GDPR, DPDP Act, CCPA - and their implications for data architecture design.
• Cloud architecture certifications (AWS, GCP, or Azure) in data or analytics specializations.

Soft Skills and Leadership Qualities:

• Exceptional communication and executive presence - able to present complex data architecture concepts with clarity and conviction to CXO and CDO audiences.
• Strong consultative mindset - listens carefully, asks the right questions, and designs solutions that genuinely address business problems rather than applying generic patterns.
• Comfortable operating in ambiguous, high-complexity environments typical of large multinational organizations with long histories and heterogeneous technology landscapes.
• Structured thinker who can decompose large, complex data problems into manageable architectural decisions and phased delivery roadmaps.
• Natural collaborator who works effectively with client teams, technology vendors, delivery managers, and internal data engineering and consulting colleagues.
• Self-driven and intellectually curious - continuously learning and applying new developments in the rapidly evolving enterprise data and AI landscape.

Skills

MDM, Python, SQL, Scala, data architect, data architecture, data modeling, data vault, dimensional modeling, ontology