Data Architect

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

Job summary

A technology firm in the UAE is seeking a Data Architect responsible for designing and implementing enterprise data architectures. You will ensure models and standards are deployed at scale and meet operational governance. The ideal candidate has strong experience in enterprise data modeling and close collaboration with engineering teams. You will own architectural decisions that impact the organization significantly and work towards improving delivery and governance standards.

Benefits

Ownership of architecture decisions

Exposure to complex enterprise systems

Meritocratic progression based on impact

Qualifications

• Proven experience in designing enterprise data architectures successfully implemented in production.
• Strong engagement during delivery phases including managing incidents.
• Ability to adhere to governance standards while maximizing efficiency.

Responsibilities

• Define and own enterprise data architecture and blueprints.
• Design and implement canonical data models and schemas.
• Establish integration patterns and governance frameworks.

Skills

Enterprise data modelling

Data integration CDC and streaming patterns

Distributed data platforms

Governance lineage and quality

Clear communication in English

Job description

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 - (content below retained):

• 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.