As a Senior Microsoft Fabric – Power BI Data Engineer, you will play a key role in building and evolving reusable, product‑oriented data and analytics solutions on Microsoft Fabric. You will work hands‑on from data ingestion and Python‑based transformations to analytics‑ready data models and Power BI semantic layers. You will design well‑structured, high‑quality Fabric reports and analytics, with strong attention to usability, clarity, and performance.
You will ensure solutions are scalable, maintainable, and standardized, avoiding one‑off custom implementations. You will apply strong engineering practices, using Git and GitHub to manage, review, and promote changes within Fabric, while collaborating closely with business and technical stakeholders to deliver trusted data products.
Key Responsibilities:
- Reporting & Data Products (Power BI/Fabric)
- Build end to end Power BI solutions:
- Semantic models
- DAX measures
- Dashboards and reports
- Focus on product thinking:
- Generic datasets reusable by multiple consumers
- Clear contract between data model and reports
- Ensure reports are:
- Performant
- Maintainable
- Aligned with business KPIs
- Aligned to the designed UI/UX
- Build end to end Power BI solutions:
- Data Modeling (Analytics Ready)
- Design scalable analytical models meant to be reused across reports:
- Star schemas (facts & dimensions)
- Conformed dimensions and standardized KPIs
- Optimize models for:
- Performance
- Governance
- Long term evolution
- Design scalable analytical models meant to be reused across reports:
- Data Engineering & Transformation (Microsoft Fabric)
- Design and implement reusable data pipelines using:
- Microsoft Fabric Lakehouse
- Dataflows Gen2
- Notebooks (Python / PySpark)
- Build production ready transformations in Python:
- Data cleansing, enrichment, aggregations
- Incremental loads, idempotent logic
- Basic data quality and validation checks
- Apply Medallion architecture principles (Bronze / Silver / Gold)
- Design and implement reusable data pipelines using:
- Engineering Practices & Product Mindset (Key Requirement)
- Work with a product oriented approach:
- Standardized data models and pipelines
- Avoid one off custom logic per consumer
- Favor configuration over customization
- Apply software engineering best practices to data:
- Modular code
- Naming conventions
- Documentation
- Contribute to shared patterns and internal data products
- Work with a product oriented approach:
- Git, GitHub & CI/CD Integration
- Use Git and GitHub as the default way of working:
- Version control for notebooks, semantic models and pipelines
- Proper branching and pull requests
- Work with GitHub integrated Microsoft Fabric:
- Code changes tracked and reviewed
- Collaboration through PRs
- Basic understanding of:
- CI/CD concepts for data & Power BI
- Promotion of changes across environments (dev / test / prod)
- Use Git and GitHub as the default way of working:
Must‑Have
- 5+ years' experience in data, BI or analytics roles
- Strong hands‑on experience with:
- Microsoft Fabric
- Power BI (semantic model, DAX, reporting)
- Python for data transformation (Pandas, basic PySpark)
- SQL
- Solid understanding of:
- Data modelling for analytics
- Data warehouse / Lakehouse concepts
- Experience using Git in a professional environment
- Engineering mindset applied to data (not only reporting)
Nice to Have (Not Mandatory)
• Experience with Azure cloud services
• Exposure to:
o CI/CD pipelines (GitHub Actions, Azure DevOps)
Microsoft Fabric expertise is a plus, but we value strong fundamentals and engineering discipline above buzzwords.
Collaborate with:
- Architects
- Product owners
- Lead Engineers
- Business stakeholders
Challenge requirements that lead to:
- Over‑customization
- Unmaintainable solutions
Promote long‑term platform quality over short‑term quick fixes
About FNZ
FNZ is committed to opening up wealth so that everyone, everywhere can invest in their future on their terms. We know the foundation to do that already exists in the wealth management industry, but complexity holds firms back.
We created wealth’s growth platform to help. We provide a global, end-to-end wealth management platform that integrates modern technology with business and investment operations. All in a regulated financial institution.
We partner with the world’s leading financial institutions, with over US$2.5 trillion in assets on platform (AoP).
Together with our clients, we empower nearly 30 million people across all wealth segments to invest in their future.
Skills Required
- 5+ years experience in data, BI or analytics roles
- Hands-on experience with Microsoft Fabric
- Power BI (semantic model, DAX, reporting)
- Python for data transformation (Pandas, basic PySpark)
- SQL
- Data modelling for analytics and data warehouse / lakehouse concepts
- Experience using Git in a professional environment
- Engineering mindset applied to data (modular code, naming, documentation)
- Experience with Azure cloud services
- Exposure to CI/CD pipelines (GitHub Actions, Azure DevOps)
FNZ Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about FNZ Group and has not been reviewed or approved by FNZ Group.
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Parental & Family Support — FNZ is described as offering 26 weeks of fully paid parental leave for both primary and secondary caregivers, alongside expanded bereavement and emergency care leave. These policies can materially increase the perceived value of the overall rewards package beyond base salary.
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Fair & Transparent Compensation — Base pay is frequently characterized as “good salary” or “nice compensation” in several markets. Paid overtime in delivery roles is also described as a meaningful boost to total earnings.
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Flexible Benefits — A flexible benefits menu is described, including options such as EV leasing, retailer discounts, and cycle-to-work offerings. This supports tailoring benefits to local needs and individual preferences where available.
FNZ Group Insights
What We Do
FNZ is committed to opening up wealth so that everyone, everywhere can invest in their future on their terms. We know the foundation to do that already exists in the wealth management industry, but complexity holds firms back. We created wealth’s growth platform to help. We provide a global, end-to-end wealth management platform that integrates modern technology with business and investment operations. All in a regulated financial institution. We partner with over 650 financial institutions and 12,000 wealth managers, with US$1.5 trillion in assets under administration (AUA). Together with our customers, we help over 20 million people from all wealth segments to invest in their future
