Accountabilities:

The Associate Architect - Data Engineer will lead the design, development, and optimization of modern data architectures that support AI-driven applications and enterprise-scale solutions.

• Design end-to-end enterprise data architecture covering ingestion, storage, transformation, orchestration, semantic layers, data serving, consumption, and governance.
• Architect solutions that integrate structured, unstructured, and graph data to support advanced AI agent workflows.
• Design multi-tenant schemas and knowledge graph models that enable large language models and intelligent systems to perform complex reasoning and data retrieval.
• Manage and optimize hybrid database environments, including cloud data platforms and specialized data solutions.
• Ensure database performance, security, scalability, and reliability for mission-critical AI and analytics workloads.
• Establish data architecture standards, governance frameworks, and technical best practices.
• Act as a technical advisor for clients by leading discovery sessions, understanding business needs, and aligning technology strategies with organizational goals.
• Define performance benchmarks for data latency, retrieval accuracy, and system efficiency.
• Develop advanced ETL and ELT strategies using batch processing, streaming, and change data capture approaches.
• Design API-first data layers and integrations that enable AI agents to securely access and use enterprise data.
• Collaborate with engineering teams to deliver scalable, secure, and innovative data solutions.

Requirements:

The ideal candidate is an experienced data engineering professional with strong architecture skills and expertise in cloud platforms, databases, and AI-enabled data solutions.

• 7+ years of experience in data engineering, data architecture, or related technical roles.
• Proven experience designing and implementing enterprise-scale cloud data architectures.
• Strong expertise with cloud lakehouse technologies such as BigQuery, Snowflake, Cosmos DB, or Kinetica.
• Experience building and managing vector databases, including solutions such as Milvus, Qdrant, Cosmos DB, or Azure AI Search.
• Strong knowledge of knowledge graph design, including property graphs, RDF schemas, and enterprise data modeling.
• Advanced understanding of ETL/ELT strategies, including streaming, batch processing, and change data capture.
• Strong database administration skills, including partitioning, indexing, sharding, optimization, and resource scaling.
• Hands-on experience designing semantic layers and AI-ready data architectures.
• Familiarity with tools such as Cube or dbt Semantic Layer is an asset.
• Knowledge of security and privacy practices, including role-based access control (RBAC) and row-level security (RLS) in AI environments.
• Experience designing API-driven data platforms and integrations for intelligent applications.
• Strong communication skills with the ability to lead technical discussions and collaborate with clients.
• Ability to work effectively in a remote environment while managing complex technical initiatives.

Benefits:

• Opportunity to work on cutting-edge AI, machine learning, cloud, and data engineering projects.
• Fully remote work environment for Canada-based employees.
• Exposure to innovative technologies and advanced AI solutions.
• Opportunity to collaborate with highly skilled technical teams and industry experts.
• Continuous learning and professional development opportunities.
• Access to emerging technologies and opportunities to expand technical expertise.
• Chance to contribute to impactful projects for leading organizations.
• Collaborative and inclusive culture focused on innovation, growth, and knowledge sharing.