We’re building AI capabilities that will transform one of the world’s largest industrial organizations from intelligent operations to next-generation industrial solutions.

Be part of this exciting journey where AI, Agentic AI, Data, Cloud, and innovation meet real-world impact at a global scale.

What makes this opportunity unique is the scale, complexity, and impact.

You will have the opportunity to:

- Build AI products and solutions that operate across a truly global enterprise.
- Work at the intersection of industry, engineering, business transformation, and technology.
- Collaborate with leading experts from ArcelorMittal and strategic technology partners.
- Help establish standards, platforms, governance, and operating models that will shape our future AI landscape.
- Convert bold ideas into production-grade solutions that create measurable business value.
- Contribute to one of the most ambitious AI transformation programs currently underway in the industrial sector.

We’re looking for passionate AI Engineers, Data Specialists, Architects, Cloud Engineers, and technology innovators who want to solve complex challenges, build solutions from the ground up, and shape what comes next.

? Ready to take your AI career to the next level? Explore our open positions and apply now on LinkedIn. Come build the future of Industrial AI with ArcelorMittal!

Job Title – Data Governance & Data Product Lead (AI)

Job Nature – Permanent

Work Location – Hyderabad

Experience – 10+ years in data management or data governance, of which 3+ years defining data products / lakehouse governance in a large enterprise

Purpose of the role:

Define and operate governed data ownership, access, quality, lineage, semantics, retention and evidence for the AI-specific Data Products and semantic models that feed ArcelorMittal's agentic AI solutions – bridging the AI CoE, the Aura/Databricks enterprise data foundation, Microsoft Fabric and the business data owners.

Key Responsibilities

- Establish Data Product governance, ownership, stewardship and lifecycle standards for AI use cases, aligned with ArcelorMittal data policies and the Aura/Databricks platform.
- Define classification, EU residency, access, retention (incl. seven-year immutable audit trail for finance reports), quality, lineage and semantic requirements.
- Run data readiness assessments for activated use cases (sources, owners, quality, legal basis) and document gaps and dependencies.
- Resolve ownership and semantic conflicts across source systems (SAP, Aura/Databricks)



and domains; govern the Microsoft Fabric semantic layer and cross-domain ontology.
- Appoint and coach Data Product Owners and Stewards in Finance and IT; maintain the ownership and stewardship matrix.
- Track data exceptions, quality debt and ownership transfer; maintain the governance evidence pack.
- Ensure ArcelorMittal Digital & IT Data representatives participate in business working sessions.

Preferred Skills

- Data governance frameworks (DAMA-DMBOK), data product / data mesh operating models, stewardship programs
- Hands-on understanding of lakehouse platforms (Databricks) and Microsoft Fabric / Power BI semantic models
- Metadata, catalog, lineage and data quality tooling (Microsoft Purview, Unity Catalog or equivalent)
- Data protection, classification, residency and retention requirements (GDPR, Sarbanes-Oxley-relevant financial data)
- Stakeholder management with business data owners, Finance and IT
- Experience defining and governing Data Products for AI, machine learning, generative AI, or agentic AI use cases, including data quality, traceability, semantic consistency, and consumption readiness
- Experience designing or governing enterprise semantic models, business glossaries, ontologies, reference data, and cross-domain business definitions
- Experience defining and operating enterprise data quality frameworks, quality KPIs, exception management, root-cause remediation, and data quality SLAs.
- Experience establishing and scaling Data Owner, Data Steward, and Data Product Owner operating models across multiple business functions.
- SAP data models (Finance & Controlling, Materials Management, master data) and SAP-to-lakehouse integration
- Experience providing governed data to AI / machine learning or retrieval-augmented generation solutions
- SQL and basic Python for data profiling
- Certifications: CDMP, Microsoft Fabric Analytics Engineer (DP-600), Databricks Data Engineer Associate
- Experience with Microsoft Fabric OneLake, semantic models, governance of self-service analytics, and enterprise Power BI deployment patterns.

Good to have skills

- AI impact assessment, human oversight, evaluation, red-teaming and lifecycle governance
- Azure security architecture,



threat modelling and secure design review
- AI/agent security including prompt injection, tool permissions, data exfiltration and content safety
- GDPR fundamentals, evidence management, risk acceptance and executive communication
- Azure AI Content Safety, Azure AI Foundry evaluations, DevSecOps and policy-as-code
- Model Risk Management, Purview, DLP, internal audit, industrial or OT security exposure
- Certifications such as IAPP AIGP, CIPP/E, ISO 42001 Lead Implementer, SC-100, AZ-500, CISSP or CCSP
- Responsible AI frameworks, EU AI Act, NIST AI RMF and ISO/IEC 42001

Qualifications

Bachelor degree in Engineering, Computer Science, Information Technology, Data, Business or a relevant discipline. Advanced degree or equivalent qualified experience is an advantage.

Deliverables

This role helps establish a permanent ArcelorMittal AI capability, embeds repeatable engineering and control practices, and reduces dependency on the implementation partner through structured ownership transfer. Success is demonstrated when:

- Every Data Product has a named owner and measurable quality; lineage and access are auditable; semantic disputes are resolved before downstream reuse; data readiness gaps are identified at Intake, not in build; EU data-residency and seven-year audit requirements for financial data are met.

- The successful Data Governance & Data Product Lead (AI) combines strong professional depth with a practical delivery mindset. The individual must be able to establish clear methods, make sound decisions, develop colleagues and progressively assume ownership from the implementation partner. Success requires confidence working across India and Europe and balanced judgement across delivery speed, reuse, security and Responsible AI.

- Data governance operating model; Data Product standard; ownership and stewardship matrix; data quality and lineage requirements; data readiness assessments; semantic governance decisions; data exception register; governance evidence pack.

Time Zone

India Standard Time (IST) with European working hours (CET/GMT) overlap

? Location: Hyderabad, India | Global Opportunities | Real-World Impact

Interested candidates can share their updated resume at [email protected]; [email protected].

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#Hiring #ArtificialIntelligence #AgenticAI #DataEngineering #Cloud #Hyderabad #ArcelorMittal #BuildTheFuture #AMDC #AMGBT

📌 Data Governance & Data Product Lead (AI) (Hyderabad)
🏢 ArcelorMittal Digital Consulting
📍 Hyderabad