Senior Data Integration Specialist
About The Position
UHN is seeking a Senior Data Integration Specialist to join a cross-functional product squad within the Data Products & Business Applications team. This role will design, build, operate and continuously improve the data pipelines, lakehouse assets, cloud infrastructure and engineering workflows that enable trusted data products and business applications for research administration and research operations. Working closely with product managers, business analysts, Salesforce administrators and developers, BI developers, data stakeholders and research operations teams, the successful candidate will help deliver scalable data pipelines and products using Microsoft Azure, Microsoft Fabric, and open source software e.g. Apache Hop. The role will support ingestion, transformation, validation and delivery of data from enterprise systems, business applications and operational workflows, with a focus on reliability, maintainability, security and practical business value.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Analytics, Health Informatics or equivalent practical experience.
- 3+ years of experience in data engineering, cloud engineering, analytics engineering, platform engineering or a related technical role.
- Hands-on experience with Microsoft Azure in a data engineering, infrastructure, integration or application delivery context.
- Hands-on experience with Microsoft Fabric or Databricks, including lakehouse-oriented data engineering, pipelines, notebooks, dataflows, warehouses or related capabilities.
- Experience working with virtual machines for development, automation, integration, deployment or operational support activities.
- Experience using source control tools such as GitHub or Bitbucket, including branching, pull requests, code review and collaborative development workflows.
- Strong understanding of data pipeline concepts, data quality, troubleshooting, environment management and operational support.
- Ability to work effectively in a cross-functional product team and document technical work clearly for technical and non-technical audiences.
Nice To Haves
- Experience building, running or supporting Docker containers for development, testing, deployment or integration workflows.
- Experience with Python and/or PySpark for data transformation, automation, testing or analytics engineering.
- Experience with SQL, Spark SQL, Delta Lake, medallion architecture patterns or lakehouse-based data modelling.
- Experience supporting Power BI reports, semantic models, or analytics products used by business teams.
Responsibilities
- Design, build and maintain data pipelines, lakehouse assets and curated data products in Microsoft Fabric.
- Develop reliable ingestion and transformation patterns for structured data from enterprise systems, business applications and operational data sources.
- Use Microsoft Azure services to support secure, scalable and maintainable data engineering solutions.
- Configure, manage and support virtual machines required for development, integration, automation or supporting tooling.
- Build, run and maintain Docker containers for repeatable development, testing, deployment or integration workflows.
- Use source control tools such as GitHub or Bitbucket to manage data engineering code, configuration and documentation.
- Troubleshoot data pipeline, integration, environment and performance issues, while supporting data quality, observability and documentation.
- Work as part of a cross-functional product squad with product managers, business analysts, Salesforce, Power BI and application stakeholders to deliver integrated application and analytics use cases.
Benefits
- Competitive offer packages
- Government organization and a member of the Healthcare of Ontario Pension Plan (HOOPP)
- Close access to Transit and UHN shuttle service
- A flexible work environment
- Opportunities for development and promotions within a large organization
- Additional perks (multiple corporate discounts including: travel, restaurants, parking, phone plans, auto insurance discounts, on-site gyms, etc.)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
