Senior Data Engineer

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 environment 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.

Design and implement end-to-end data architectures and production-grade pipelines for various clients. Act as a technical advisor to stakeholders to translate business requirements into scalable data solutions.

Requires over 7 years of professional data engineering experience with deep knowledge of distributed systems and modern data platforms. Proficiency in Python, SQL, and various orchestration and streaming technologies is essential.

• SQLPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Data Architecture
• Microsoft Fabric
• Python
• SQL
• Spark
• Kafka
• Databricks
• Snowflake
• Azure Data Factory
• Airflow
• Data Modeling
• Distributed Systems
• Streaming Pipelines
• Lakehouse Architecture
• Client Advisory
• Feature Engineering

• Data & Analytics
• Consulting
• Engineering
• Technology
• Software

Minimum experience

5+ years

Apply by

Sep 9, 2026

Posting language

English

Working hours

40 hours per week

Location requirements

Country, Montreal, Quebec, Canada

Seniority

Mid-Senior level

Application method

Direct apply is available