Role Purpose

We're looking for a very senior Data Architect to lead the enterprise data architecture for EET Fuels, a UK refinery defining the standards, governance and blueprint that let a growing Microsoft Fabric platform scale with confidence. You'll turn business ambition for better insight into well-governed, trusted data products, lead a small team, and bring together operational (OT) and enterprise (IT) data across a safety-critical industrial environment.

Key Responsibilities

Data Strategy & Enterprise Architecture

- Own the data architecture vision, strategy and maturity roadmap, ensuring every design decision is anchored to a specific business problem and aligned to enterprise-wide standards and principles.

- Design data architecture on Microsoft Fabric as the primary platform (with Databricks for advanced engineering and AI workloads), building a scalable, future-proof blueprint that grows with the business.

- Partner proactively with project teams and business stakeholders to ensure data is designed in from the outset of every new initiative.

- Architect the integration of OT and IT data (PI System, DCS, SAP and enterprise systems), reflecting the specific realities and safety requirements of refinery operations.

Translating Business Ambition into Data Reality

- Partner directly with business departments to shape ambitious but loosely defined ideas for better insights into concrete, well-modelled data requirements and use cases.

- Champion a data product mindset ensuring key datasets are treated as owned, documented, quality-assured products with explicit consumers, and laying the groundwork for trusted self-service analytics as governance matures.

- Present clear, compelling insights to colleagues that support confident, effective use of data across the business.

- Develop and integrate data services that meet the needs of multiple business functions,



ensuring consistency and reuse as the platform scales.

- Act as a trusted advisor to business leaders influencing through insight and credibility and bringing stakeholders along on the journey.

Data Modelling & Analysis

- Direct the production of data models across multiple subject areas of the business, ensuring modelling work reflects real business rules and terminology.

- Own and maintain Enterprise (conceptual/logical) and Functional (subject-area) data models, ensuring consistency and traceability between the two.

- Ensure rigorous data profiling and source system analysis underpins every architecture and integration decision.

- Build data modelling capability within the team mentoring and upskilling engineers/analysts, and establishing modelling standards and templates that make good practice repeatable.

Governance, Standards, Cataloguing & Metadata

- Establish a data governance framework tailored to the organisation's needs, defining what's required and driving genuine adoption across the business.

- Define and implement data policies, processes and standards (naming conventions, modelling standards, integration patterns, data quality rules) aligned to a recognised framework such as DAMA-DMBOK.

- Establish and maintain a data catalogue so business users can easily discover, understand and trust what data exists making data genuinely findable and usable, not just technically governed.

- Own the metadata repository, ensuring definitions,



lineage and ownership remain accurate and genuinely useful to the business.

- Ensure architecture and governance decisions reflect UK regulatory obligations (UK GDPR) and the safety-critical nature of refinery operational data.

Leadership & Stakeholder Engagement

- Lead and develop a small, high-performing team of engineers, setting direction and quality standards for their work.

- Communicate with equal confidence to technical stakeholders and business stakeholders.

- Provide architecture consulting to senior leadership and present strategy, roadmaps and progress at CXO level.

- Track emerging data trends, tools and technologies (including AI/ML readiness) and shape the roadmap accordingly.

Experience Required

15+ years in enterprise data architecture, including experience building a data architecture function or governance capability, ideally in a greenfield or early-maturity environment.

- Strong grounding in data modelling (conceptual, logical, physical), data profiling and source system analysis.

- Proven track record establishing data governance, standards and metadata management practices that are genuinely adopted, not just documented.

- Experience implementing data cataloguing practices and tooling, and familiarity with data product/data mesh thinking as an operating model.

- Strong working knowledge of Microsoft Fabric (Lakehouse, Medallion Architecture, semantic models) and Databricks, with the ability to set direction and review architecture decisions confidently.

- Demonstrated ability to influence senior/CXO stakeholders and translate ambiguous business needs into concrete data requirements.

- Proven people leadership experience, having built and led a technical team.

- Strong awareness of UK regulatory context (UK GDPR) and experience operating in safety-critical industrial environments.

📌 Enterprise Data Architect (Navi Mumbai)
🏢 Essar Uk Services
📍 Navi Mumbai