Data Architect

Role overview

We are looking for a Data Architect to take ownership of the full data architecture for operational and analytics workloads inside a data centre setting. The position focuses on industrial data capture, data modelling, analytics readiness, and built-in governance, converting OT data such as OPC UA, BMS, and PQMS telemetry into dependable insights that the business can use.

This is a practical architecture role with responsibility for setting standards, developing key elements of the data platform, and keeping production systems stable. You will also act as the technical lead for OT ingestion, analytics architecture, and embedded data governance.

Key responsibilities

• Design, implement, and run OPC UA-driven ingestion pipelines from BMS, PQMS, PLC, and sensor sources.
• Build edge and on-premises data pipelines suited to data centre operations.
• Oversee raw and curated data layers while maintaining reliability, consistency, and strong performance.
• Solve time-series challenges such as sampling frequency, timestamps, aggregation, and delayed data arrival.
• Track, diagnose, and improve live production pipelines.
• Own the full architecture from OT source systems through to analytics consumption.
• Set standards for OPC UA connectivity, subscriptions, streaming and batch patterns, buffering, retry logic, and fault tolerance.
• Create architecture rules for time-series schemas, asset and tag hierarchies, naming standards, and metadata structures.
• Define non-functional expectations covering availability, resilience, latency, performance, scalability, and OT/IT security.
• Provide technical direction on architecture and design choices.
• Convert curated OT data into fact and dimension models ready for analytics.
• Design and maintain data marts and datasets used for dashboards and reporting.
• Govern the analytics and semantic layer so KPIs are used consistently.
• Set standards for metric logic, data grain, time windows, and aggregation behaviour.
• Support a single trusted source of truth for business metrics and reduce duplicated calculations.
• Enable self-service analytics through clear, documented, trusted datasets.
• Build governance into pipelines and analytics models, including ownership, domain mapping, technical metadata, and access controls.
• Define and enforce data quality checks for completeness, validity, and timeliness.
• Maintain lineage and traceability from OT systems to business KPI outputs.
• Keep documentation current to support transparency and audit readiness.
• Work with stakeholders to ensure the data produced is suitable for its intended use.
• Partner with analysts and business stakeholders to translate requirements into scalable analytics solutions.
• Check that outputs reflect both business intent and operational reality.
• Advise teams on data usage, limitations, and interpretation.
• Continuously improve the data platform and analytics ecosystem.

Required experience and skills

• Substantial experience in data architecture, data engineering, analytics engineering, or industrial data platforms, typically built over several years of progressive responsibility.
• Practical expertise with OPC UA, including clients, servers, security, certificates, and subscriptions.
• Background with BMS, PQMS, SCADA, or similar industrial telemetry systems.
• Strong Python development ability and solid SQL knowledge.
• Experience with streaming and messaging tools such as Kafka, MQTT, or similar technologies.
• Good understanding of time-series data design and modelling.
• Experience operating in on-premises or data centre environments.
• Hands-on exposure to data quality, lineage, metadata, metric governance, or semantic modelling.
• Ability to manage architecture, delivery, and operational priorities at the same time.

Preferred experience

• Exposure to hybrid cloud plus on-premises data architectures.
• Industry experience in energy, facilities, or data centre operations.
• Familiarity with analytics or machine learning use cases built on operational data.
• Experience creating enterprise KPIs or analytics standards.

Benefits

• Flexible working arrangements.
• A complete range of health and wellness benefits.
• Ongoing learning and development opportunities.
• Internal mobility pathways.

Additional information

This role is based in Singapore and is a full-time, onsite position. The opportunity is for someone who can lead technically while also contributing hands-on to delivery and operations.