About the Company

This global data and machine learning consultancy works with organizations across multiple industries to design and deliver modern data platforms. Projects span data engineering, analytics, AI, and large-scale processing environments.

The work is client-facing and technically varied, with engineers moving between different technology stacks and solving platform challenges from architecture through production delivery.

The Role

This is a senior data engineering role for someone comfortable operating as both an engineer and technical advisor. You will design modern data architectures, build production-grade pipelines, and work directly with client stakeholders to turn business requirements into scalable data solutions.

What You Will Do

- Design end-to-end data architectures covering ingestion, storage, processing, and downstream analytics or AI workloads.
- Build and operate modern data platforms, with Microsoft Fabric as a core setting alongside client-specific technologies.
- Develop resilient batch and streaming pipelines, including the orchestration, monitoring, and automation needed to run them in production.
- Define data models using approaches such as Star, Snowflake, and Data Vault, with strong validation and data quality practices.
- Work directly with client stakeholders and data science teams on technical trade-offs, solution design,



feature engineering, and low-latency data requirements.

What You Bring

- 7+ years of professional data engineering experience, including client-facing work or delivery across multiple projects, industries, or technology environments.
- Deep data engineering fundamentals, including distributed systems, consistency models, the CAP theorem, and large-scale data processing.
- Strong experience with modern data platforms such as Microsoft Fabric, Databricks, or Snowflake, plus orchestration tools including Azure Data Factory, Airflow, Dagster, or Prefect.
- Hands-on experience with lakehouse architecture, distributed processing, and streaming technologies such as Spark, Flink, Kafka, Event Hubs, or Spark Streaming.
- Advanced Python and SQL skills, experience across relational and NoSQL databases, and the communication skills to handle architecture discussions, solution scoping, client expectations, and pre-sales work.

Why This Role

You will work across architecture, hands-on engineering, and client advisory rather than being limited to pipeline development. The scope covers modern cloud data platforms, distributed processing, streaming, and AI-ready data systems, with the variety that comes from solving different technical problems across multiple client environments.

📌 Senior Data Engineer (Montreal)
🏢 TekRek
📍 Montreal