Our team is hiring a Senior Sensor Fusion & Data Architecture Lead to join our growing team on one of Canada’s most important airport projects. The successful candidate will be the authoritative lead for operational and engineering data across the program, bringing deep expertise in OT and Industrial IIoT architectures, edge computing, cloud architectures, and data transformation. Define airport Programs of Requirements (PoRs) for utilities, energy metering, environmental and condition monitoring, and OT/industrial control system data outputs.

Classify types and classes of data produced by OT, IT, infrastructure, and facilities systems. Establish standards for centralizing data in the corporate Data Hub versus maintaining it locally in systems of record. Work closely with enterprise and solution architects to design Event‑Driven Architecture (EDA) – validating event suitability, defining semantics, structure, metadata, and ensuring publishing frequency matches operational reality.

Act as the bridge between engineering teams, OT vendors, data platforms, and analytics teams. Lead the identification of data points across people, assets, infrastructure, and systems to support reliability engineering, predictive maintenance, capacity optimization, digital twin, and simulation use cases. Serve as the airport’s technical authority on data access and structure with OEMs and system vendors, leading discussions on integration constraints, data ownership, and access rights.

Prototype analytics, simulations, or models to test data sufficiency, validate assumptions, and demonstrate operational value.

Program Of

Requirements & Data Design Leadership Develop PoRs for utility and energy metering, Central Utilities Plant (CUP), environmental and condition monitoring, and OT/industrial control system data outputs. Define data requirements at the design stage, not retrofitted post‑construction.

Ensure

PoRs articulate what is measured, why it is measured, expected accuracy, resolution, frequency, and where the data terminates.



Data Classification & Governance (OT/IT) Establish a practical classification model for operational versus analytical data, real‑time versus near‑real‑time versus historical, control vs telemetry versus events. Define data ownership boundaries, identifying data that must remain within OT systems (e.g., PLC/SCADA) and data that should be published to corporate platforms.

Partner with enterprise data governance to embed privacy, security, and lifecycle controls by design. Event‑Driven Architecture Alignment Validate data points suitable for events. Combine people‑based sensing, machine data, and enterprise context to enable reliability engineering, predictive maintenance, capacity optimization, and digital twin and simulation use cases.

Lead discussions on data outputs, integration constraints, and vendor‑provided system alignment with long‑term architecture. Rapidly prototype analytics, simulations, or models to test data sufficiency, validate assumptions, and demonstrate operational value. Hands‑on experience with OT/IoT/industrial or asset systems.

Experience with spatiotemporal, sensor, or time‑series data. Enterprise data and systems architecture experience in complex operational environments. Real‑time and streaming data architectures. Cloud and edge architectures (Azure strongly preferred).

Solid

Python and SQL capabilities. Digital twin, simulation, or agent‑based modelling. Applied data science or ML in operational environments. Vendor negotiation and data‑access governance.

Personal Attributes

Comfortable operating between engineering, IT, architecture, and business stakeholders. Pragmatic understanding of data strategy and democratization. Clear communicator who translates physical system capabilities into digital strategies. Base salaries are determined according to skill, experience, and impact, with internal and external competitiveness taken into account.

Benefits include competitive compensation, employee recognition, flexible benefits for health, wellbeing, and financial needs, training and professional development, hybrid working culture, and generous time‑off policies. #

📌 Senior Data Engineer (H/F) (IT)
🏢 AtkinsRéalis
📍 Toronto