Senior Data Architect modernizing Alberta justice data marts into an integrated enterprise data warehouse. Designing ETL, Power BI testing, data models, governance, and reporting architecture.
About the role
- Associate Architect Data Engineer spearheading development of innovative data layers for Agentic AI. Collaborating on hybrid-database environments across Snowflake and Kinetica, driving client technical strategy.
Responsibilities
- Spearhead the structural development of an innovative data layer tailored for Agentic AI.
- Orchestrate hybrid-database environments across Snowflake and Kinetica while acting as the cornerstone for client technical strategy and governance.
- Design the end-to-end blueprint for a modern enterprise data architecture encompassing all layers such as Ingestion Management, Lakehouse storage, Transformation & Orchestration, Semantic & Context, Serving & Consumption, Governance, and seamlessly integrating structured, unstructured, and graph data for consumption by AI agents.
- Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval.
- Oversee the health, security, and performance optimization of data clusters (BigQuery/Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows.
- Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives.
- Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic execution.
Requirements
- 7+ years of experience in Data Engineering/Architecture.
- Proven expertise in architecting for cloud lakehouses (BigQuery / Cosmos / Snowflake / Kinetica) and building Vector DBs (Milvus / Qdrant / Cosmos / Azure AI Search).
- Ability to design Property Graphs or RDF schemas that map enterprise entities to serve complex clinical traversal queries.
- Deep knowledge of data orchestration patterns (Change Data Capture, Streaming, and Batch) to ensure data freshness.
- Strong DBA skills—partitioning strategies, indexing, sharding, vacuuming, and resource scaling in cloud-native environments.
- Hands-on experience with vector stores, knowledge graphs, and semantic layer design to enable intelligent agent workflows.
- Experience with tools like Cube or dbt Semantic Layer to provide a consistent "Language" for AI agents to query.
- Knowledge of RBAC and Row-Level Security (RLS) within an AI context—ensuring agents only "see" what they are authorized to access.
- Experience designing API-first data layers that agents can use as "Tools" (e.g., function calling).
Benefits
- Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
- Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
- Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
- Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
- If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !
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Senior Data Architect integrating Alberta court data marts into an enterprise data warehouse. Designing ETL, data models, governance practices, and Power BI validation reports.
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