We are seeking a talented and proactive Data Engineer for an enterprise-level contract opportunity based in Montreal, Canada. In this role, you will take on a vital data engineering, cloud analytics, and business intelligence enablement capacity, specializing in designing scalable data models, building robust cloud data pipelines, and transforming enterprise data into high-value analytical assets.
Operating within a hybrid model in Montreal, you will bridge the gap between transactional enterprise systems and up-to-date cloud analytics platforms. You will engineer and optimize data pipelines using Snowflake, Matillion, and AWS cloud services, while modeling complex enterprise data structures including SAP data into clean, dimensional models. Additionally, you will support cross-functional reporting across Tableau and Power BI and maintain data integration applications. This position demands an experienced data engineering practitioner with advanced SQL capabilities, solid cloud data warehousing expertise, and strong problem-solving skills to deliver reliable, production-grade data solutions.

Location:
Montreal, CanadaAssignment Type: Hybrid (3 days onsite, 2 days remote per week)Contract Duration: 6-month contract (with extension potential)Avantages
Modern Cloud Stack: Build and manage data pipelines using Snowflake, Matillion, and AWS cloud services.
Enterprise Data Integration: Model and transform complex transactional data from SAP ECC and S/4HANA systems.
Balanced Hybrid Model: Enjoy flexibility with a structured schedule of 3 days onsite and 2 days remote.
End-to-End Ownership: Work across the full lifecycle from data modeling and ETL engineering to BI dashboard enablement.
Responsabilités
Design dimensional and analytical data models utilizing star and snowflake schemas to establish scalable,



high-performance data architectures.
Build, schedule, and optimize enterprise ETL and ELT data pipelines utilizing Matillion.
Develop, tune, and maintain advanced SQL queries, views, stored procedures, and analytical data transformations in Snowflake.
Utilize AWS cloud services—including S3 data storage, compute instances, SQS message queues, SNS notifications, and Lambda functions—to support data ingestion and processing workflows.
Model and transform complex transactional data from enterprise systems like SAP ECC and S/4HANA into standardized, business-friendly analytical structures.
Create, optimize, and maintain interactive visual dashboards and operational reports in Tableau and Microsoft Power BI to deliver actionable insights.
Collaborate closely with business stakeholders to elicit reporting requirements, define key performance indicators (KPIs), and deliver scalable data-driven solutions.
Develop, enhance, and support applications using ASP.
NET to facilitate reporting needs and custom data integration workflows.
Support ongoing organizational rebranding initiatives, system transitions, and reporting updates.
Utilize Jira and Confluence to manage Agile sprint planning, backlog refinement, task execution, and technical documentation.
Conduct data validation, reconciliation checks, and quality assurance testing across data pipelines and reporting outputs.
Qualifications
Core Technical & Data Engineering Requirements




Professional

Experience:
Minimum 3+ years of full-time professional experience in Data Engineering, Business Intelligence, or Analytics Engineering.
Advanced SQL & Data Modeling: Expert-level SQL querying and query optimization skills, with proven experience designing dimensional star and snowflake data models.
Cloud Data Warehousing: Solid hands-on experience developing and managing data models within the Snowflake data warehouse platform.
ETL/ELT Tools: Proven practical experience building and optimizing data transformation pipelines using Matillion.
AWS Cloud Services: Practical proficiency utilizing core AWS cloud services, including storage, compute, SQS, SNS, and AWS Lambda.
SAP Data Structures: Hands-on experience analyzing and modeling transactional data from SAP ECC or SAP S/4HANA systems.
Data Visualization: Familiarity with developing reports and interactive dashboards in Tableau and Microsoft Power BI.
Application Development: Practical experience with ASP.
NET or general web application development supporting data integration.
Preferred Technical Assets & Methodologies
Certifications: Snowflake certification or AWS analytics certifications are considered an asset.
Advanced Analytics & Scripting: Experience with DAX modeling in Power BI, Python scripting for data automation, or Git version control workflows.
Emerging Technologies: Foundational knowledge of Machine Learning concepts and Large Language Models (LLMs) is considered a plus for long-term initiatives.
Industry Background: Prior experience working within manufacturing or energy industry sectors.
Soft Skills & Delivery Attributes
Agile Collaboration: Demonstrated experience working effectively within Agile/Scrum delivery teams an

📌 Data Engineer (Winnipeg)
🏢 Randstad
📍 Winnipeg