Data Architect

Overview

This is not a conceptual architecture role.

As a Data Architect at Sentra

AI, 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.

Sentra

AI 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.

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.

• 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.

• 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.

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.

• 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

• 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

Sentra

AI 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.