Power BI Analytics Engineer
Posted 22 Sep 2026
Advertised as “Senior Power BI Analytics Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 6+ yrs
- Management level
- Individual contributor
- Visa sponsorship
- Not offered
No salary listed for this role.
Field of studyComputer Science, Information Systems (or related)
Study levelBachelor's or higher
Build the Future with AspenView Technology Partners
At AspenView, we are passionate about transforming the way organizations approach technology. We specialize in creating high-performing, nearshore IT teams to help North American clients innovate faster and more efficiently.
As we continue to grow, we’re looking for exceptional people to join our team and help drive impactful change across industries.
About the Role
AspenView is looking for a Senior Power BI Analytics Engineer to design, build, and optimize the reporting and data modelling layer that enterprise stakeholders rely on to make decisions. You will work end-to-end — from requirements gathering with analysts and business stakeholders, through dimensional modelling and pipeline development in the Azure ecosystem, to the Power BI reports that surface the result.
This is a contributor role, not a task-execution role. The team already has people who deliver what they are handed. What it needs is someone who questions whether the right thing is being built, and says so — to peers and to senior stakeholders alike. You will be expected to challenge incumbent patterns, surface risk early, and leave the team’s practice stronger than you found it.
What You Will Do
- Design and build Power BI reports using data modelling, Power Query, and DAX.
- Run analysis and requirements gathering to translate business logic into data solutions.
- Communicate effectively with data analysts, BI developers, and business stakeholders.
Data Modelling and Architecture
- Design and implement scalable data marts and BI data models in Azure Data Factory and Microsoft Fabric using dimensional modelling principles (star and snowflake schema). • Implement strategies to manage historical data and slowly changing dimensions (SCD types 1, 2, and 3).
- Design and document data lineage, transformations, and architecture components. Pipeline Development and Optimization
- Develop and manage ETL/ELT pipelines supporting both batch processing and near real-time data ingestion.
- Optimize Azure Data Factory objects — tables, views, and warehouses — for performance and cost efficiency.
- Monitor, troubleshoot, and ensure the reliability and accuracy of data pipelines and models. Governance and Ways of Working
- Implement best practices for data governance, security, and compliance.
- Work fluently within Azure DevOps and Agile / Scrum methodologies.