Data Engineer | Onsite | Canada | CAD Salary

About client:
A global IT and consulting company based in Bangalore, India providing IT services to clients worldwide across multiple industries.

Opening: Data Engineer 

Job Description
Responsibilities:

• 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.

Experience Required: 5 years to 7+ years

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).


Other Details:
Experience: 5-7 years
Work Timings: 9am-6pm
Work Days: Monday- Friday
Work Mode: Onsite
Location: Brampton, Ontario, Canada

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