Opens LinkedIn
- Employment type
- Full-time
- Experience level
- Mid-level · 3+ years
- Minimum education
- College diploma
- Apply by
- Oct 21, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Not Applicable
Job summary
Design, develop, maintain, and optimize scalable data pipelines and infrastructure, ensuring enterprise data is accurate, secure, and reliable. Collaborate with stakeholders and engineering and operations teams to address data requirements, troubleshoot issues, perform root cause analysis, and support cloud-based data engineering initiatives.
Job details
Responsible for building, maintaining, and optimizing data pipelines while ensuring the accuracy, security, and reliability of enterprise data. The position combines cloud-based data engineering, analytics, troubleshooting, and collaboration with technical and operational teams to deliver scalable data solutions and support business initiatives. Client Details A company in the industrial and manufacturing industry located in Winnipeg. Description Design, develop, and maintain scalable data pipelines for various data sources. Collaborate with stakeholders to understand data requirements and optimize data workflows. Review existing operations data, research open issues, and collaborate with the engineering and operations teams on new and ongoing projects. Design tools and infrastructure to analyze large volumes of data. Assist the team with troubleshooting, root cause analysis, and thorough defect resolution in the event of a problem. Provide expertise on cloud-based data engineering best practices. Profile The successful candidate will possess 3+ years of experience as a Data Engineer or in a similar role, with strong expertise in Python, PySpark, SQL, ETL development, and Microsoft data technologies. Proficiency in Python, PySpark, data modeling, ETL processes and data integration using Microsoft technologies. Advanced SQL skills for data transformation and querying on Azure data services (e.g., Data Factory, Databricks, Synapse, Fabric, Purview). The ideal professional will be capable of designing scalable data pipelines, troubleshooting complex issues, conducting root cause analysis, and supporting cloud-based data engineering initiatives. They will demonstrate sound technical judgment, attention to data quality and security, and familiarity with DevOps and CI/CD practices. Degree or Diploma in Computer Science, Data Engineering, Information Systems, or related field. 3+ years of experience as a Data Engineer or similar role. Job Offer Opportunity to work with leading Microsoft Azure data technologies and modern cloud platforms. Exposure to end-to-end data engineering projects, from design and development to optimization and support. A visible role collaborating with engineering and operations teams on business-critical initiatives. Continuous learning opportunities across big data, analytics, DevOps, and cloud engineering best practices. The ability to make a direct impact on data quality, reliability, security, and organizational decision-making. MPI does not discriminate on the basis of race, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, or based on an individual's status in any group or class otherwise protected under applicable human rights legislation. MPI encourages applications from minorities, women, the disabled and all other qualified applicants
What you’ll do
Design, develop, maintain, and optimize scalable data pipelines and infrastructure, ensuring enterprise data is accurate, secure, and reliable. Collaborate with stakeholders and engineering and operations teams to address data requirements, troubleshoot issues, perform root cause analysis, and support cloud-based data engineering initiatives.
Requirements
Requires a degree or diploma in Computer Science, Data Engineering, Information Systems, or a related field, plus at least three years of experience as a Data Engineer or in a similar role. Candidates should have strong Python, PySpark, SQL, ETL, data modeling, and Microsoft Azure data technology skills, along with familiarity with DevOps and CI/CD practices.
Benefits
- Continuous Learning Opportunities
- Exposure To End-To-End Data Engineering Projects
- Opportunity To Work With Microsoft Azure Data Technologies
- Direct Impact On Data Quality And Organizational Decision-Making
Listed skills
- Python · Preferred
- SQL · Preferred
- Microsoft Azure · Preferred
- Root Cause Analysis · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- PySpark
- SQL
- ETL Development
- Data Modeling
- Data Integration
- Microsoft Azure
- Azure Data Factory
- Azure Databricks
- Azure Synapse
- Microsoft Fabric
- Microsoft Purview
- Data Pipeline Development
- Root Cause Analysis
- Data Quality
- DevOps And CI/CD
Job areas
- Data & Analytics
- Technology
- Software
- Manufacturing
- Engineering
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