Senior Data Engineer

Position: Senior Data Engineer Location: Brampton, Ontario, Canada, Onsite Duration: Long Term Contract Detailed JD (Roles and Responsibilities) Job Description: What You Will Do: Data Pipelines: Build ETL flows for structured/unstructured data, ensuring normalization, deduplication, and semantic consistency. Vector Infrastructure: Manage pgvector, Azure AI Search, Redis vector indexing, and hybrid search layers. Data Governance: Implement zero-trust access, privacy controls, and compliance within AI context pipelines. Real-time Processing: Build event-driven architectures that continuously refresh embeddings and indexes. Required Qualifications: Deep experience with distributed data systems, SQL, and orchestration tools. Experience tuning high-throughput database infrastructure. Knowledge of Google’s GECX is a plus. Familiarity with chunking strategies and embedding models. Skillset Requirements: ETL & Data Modeling: Designing pipelines for structured/unstructured data, normalization, deduplication, and semantic consistency. Vector Databases: pgvector, Redis, Azure AI Search, hybrid search, and index optimization. Distributed Data Systems: Kafka, Spark, Flink, or similar event-driven architectures. Data Governance: Zero-trust access, privacy controls, compliance, and auditability. Real-time Embedding Updates: Event-driven refresh pipelines for RAG and agent memory systems. Chunking & Embeddings: Semantic chunking, metadata tagging, and embedding model selection. Search Infrastructure: BM25, hybrid search, inverted indexes, and ranking algorithms. Performance Tuning: High-throughput read/write optimization. Data Quality & Lineage: Validation, schema enforcement, and lineage tracking (e.g., Great Expectations, OpenLineage).

Build and manage ETL pipelines for structured and unstructured data while ensuring semantic consistency and normalization. Develop vector infrastructure and event-driven architectures to support real-time embedding updates for RAG and agent memory systems.

Requires deep expertise in distributed data systems, SQL, and orchestration tools with a focus on high-throughput database tuning. Candidates should be familiar with chunking strategies, embedding models, and data governance frameworks.

• SQLPreferred
• RedisPreferred

Identified from the job description. Confirm important requirements above.

• ETL
• Data Modeling
• Pgvector
• Redis
• Azure AI Search
• Kafka
• Spark
• Flink
• Zero-trust Access
• RAG
• Semantic Chunking
• BM25
• Performance Tuning
• Data Lineage
• SQL
• Distributed Data Systems

• Data & Analytics
• Technology
• Software
• Engineering

Minimum experience

5+ years

Apply by

Sep 5, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available