Data Architect

SentraAI; Dubai; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading AI solutions provider in Dubai is seeking a skilled Data Architect to define and own data architectures within enterprise environments. The role demands expertise in designing enterprise data models, ensuring governance and quality, and supporting engineering teams. Successful candidates will have a background in large-scale data systems and a commitment to delivering architecture that is both practical and effective. This position offers significant responsibility and the chance to shape impactful systems.

Benefits

Meritocratic progression based on impact

Exposure to large-scale systems

Valued delivery over theory

Qualifications

• Strong understanding of lakehouse architectures and data governance in live environments.
• Ability to explain architectural decisions to both technical and non-technical stakeholders.

Responsibilities

• Define enterprise data architecture and target-state blueprints.
• Design data models spanning core domains and shared entities.
• Establish governance and quality standards for data architectures.
• Support engineering teams during implementation and explain trade-offs.

Skills

Enterprise data modelling

Distributed data platforms

Data integration

Governance and quality

Clear communication in English

Job description

Overview

This is not a conceptual architecture role.

As a Data Architect at SentraAI, you will define and own data architectures that are built, deployed, audited, and relied upon in large, complex enterprise environments. The models, patterns, and standards you design will be implemented at scale and tested under real operational pressure.

If your experience is limited to frameworks, PowerPoint, or advisory-only work, this role is not for you.

The Operating Context

SentraAI is delivering a large-scale data and AI transformation for a complex enterprise operating under high governance and reliability expectations.

The programme involves:

• Migrating fragmented legacy data estates into a modern cloud-native lakehouse
• Designing enterprise-wide data models that support operational, analytical, and AI use cases
• Enabling real-time and batch data processing across many domains and systems
• Establishing governance, lineage, and quality standards that work in practice

This is not greenfield. The architecture must survive delivery, scale, and scrutiny.

Your Accountability

You are accountable for architecture that works in reality, not theory.

That includes:

• Defining the enterprise data architecture and target-state blueprints
• Designing canonical data models and domain-aligned schemas
• Establishing lakehouse layering, data contracts, and integration patterns
• Ensuring governance, lineage, and quality are embedded, not bolted on
• Translating architectural intent into delivery-ready standards
• Supporting engineering teams through implementation and trade-offs
• Explaining architectural decisions clearly to technical and non-technical stakeholders

Ownership does not end once diagrams are approved.

Requirements

What You Will Design

• Enterprise data models spanning core domains and shared entities
• Lakehouse architectures supporting batch, streaming, and AI workloads
• Integration patterns for source systems, CDC, and event-driven pipelines
• Data governance frameworks covering cataloguing, lineage, access, and quality
• Reference architectures that engineers can actually build and operate

You are expected to use AI tools to accelerate design, documentation, validation, and decision-making, while operating within defined governance standards.

This Role Is Not For You If

• You have not seen your architectures implemented in production
• You avoid engagement during delivery or incidents
• You treat governance as a documentation exercise
• You design without regard for cost, operability, or scale
• You struggle to explain trade-offs clearly under pressure

We are explicit because credibility matters.

What Strong Looks Like

Within 6–12 months:

• Engineers follow your standards because they work
• Data models are stable, extensible, and trusted
• Governance improves delivery speed rather than slowing it
• Architectural decisions reduce complexity over time
• Stakeholders trust your judgement, not just your diagrams

This is how performance is measured.

What We Expect You To Be Strong At

• Enterprise data modelling, conceptual to physical
• Distributed data platforms and lakehouse architectures
• Data integration, CDC, and streaming patterns
• Governance, lineage, and quality in live environments
• Working closely with engineers under real delivery constraints
• Clear, confident communication in professional English

Benefits

What SentraAI Gives in Return

• Ownership of architecture decisions that matter
• Exposure to large-scale, complex enterprise systems
• A team that values delivery over theory
• Meritocratic progression based on impact
• Career capital that is globally credible

Final Note

SentraAI does not hire architects to produce documentation.

We hire architects to shape systems that last.

If you want to design data architectures that are built, operated, and trusted at scale, we should talk.