Principal Enterprise Data Architect – Semantic Web & Middleware

Job Title: Principal Enterprise Data Architect – Semantic Web & Middleware

Location: Montreal, Canada - Hybrid

Duration: Contract

Job Description:

Role Overview

We are seeking a visionary Principal Enterprise Data Architect to spearhead the design, governance, and scaling of our next-generation data platform. In this highly specialized role, you will lead the convergence of three critical domains: Semantic Web Technologies (RDF Triple Stores), Enterprise Middleware, and End-to-End Data Architecture .

You will design scalable knowledge graphs, construct the high-throughput middleware networks that route semantic data, and establish the overarching architectural blueprints that transform raw enterprise data into linked, machine-understandable assets.

🛠️ Core Responsibilities

Semantic Web & Ontological Engineering

• Design, implement, and scale production-grade RDF Triple Stores and Graph Databases to power enterprise knowledge graphs.
• Develop and govern semantic models , including core ontologies, taxonomies, and metadata vocabularies using OWL, RDFS, and SKOS .
• Optimize highly complex SPARQL queries , graph traversals, and semantic reasoning engines to ensure low-latency data access.

Middleware Architecture & Integration

• Architect enterprise middleware layers (message brokers, event-streaming fabrics, and API gateways) engineered specifically to handle linked data, RDF graphs, and JSON-LD payloads.
• Design robust ETL/ELT abstraction layers that map and lift structured, semi-structured, and relational data into semantic RDF triple formats (R2RML).
• Ensure high-availability (HA) , replication, horizontal scaling, and disaster recovery configurations across all middleware runtime platforms and triple store clusters.

Strategic Data Architecture

• Define the long-term data architecture strategy , reference models, and technical standards across cloud, hybrid, and on-premises environments.
• Enforce strong data governance frameworks , access controls, data provenance, and deterministic data lineage tracing protocols across graph structures.
• Collaborate with business executives, product owners, and engineering leads to turn architectural patterns into production-ready pipelines.

📋 Role Requirements

Technical Skills

Semantic Technologies & RDF

• Graph Ecosystems: Mastery of enterprise RDF Triple Stores and Graph Platforms (e.g., GraphDB, Stardog, Virtuoso, AWS Neptune, or Apache Jena).
• Graph Standards: Expert-level command of RDF, SPARQL, OWL, SHACL (for graph validation), and serialization formats ( Turtle, JSON-LD, N-Triples ).

Middleware & Infrastructure

• Event & Message Fabric: Deep experience with streaming and messaging systems ( Apache Kafka, RabbitMQ, Confluent, or IBM MQ ).
• Data Integration: Strong proficiency with data routing orchestration engines (e.g., Apache NiFi, Airflow, or MuleSoft) and semantic transformation frameworks.
• Programming: Competency in Python, Java, or Scala for building custom semantic connectors and middleware logic.

Core Data Architecture

• Data Modeling: Proven experience spanning relational modeling (RDBMS), NoSQL, dimensional modeling, and semantic graph modeling.
• Enterprise Practices: Familiarity with framework methodologies like TOGAF, Zachman, or SABSA .

Experience & Qualifications

• Education: Master’s or Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related quantitative field.
• Experience: 8+ years in data engineering and architecture, with at least 3+ years designing production-grade semantic graph systems and middleware fabrics.
• Leadership: Exceptional cross-functional leadership and communication skills, with a track record of driving large-scale data transformation initiatives.