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Solutions One
Data Engineer / BI Analyst – Microsoft Fabric & Power BI
Remote
(Anywhere)
Salary Range
Not informed
Experience Level
Mid level
Requirements
Tasks and Responsibilities
We are looking for a professional with strong data knowledge to work on building and maintaining pipelines, data modeling, and developing dashboards and reports using the Microsoft ecosystem, with a focus on Microsoft Fabric and Power BI.
Additionally, this person should have basic knowledge of database administration (DBA), supporting optimization and maintenance activities in SQL environments.
Although the role includes database activities, the main focus of the position is data engineering and BI. DBA responsibilities represent a smaller portion of the scope.
Main responsibilities
• Develop and maintain data pipelines (ETL/ELT) in Microsoft Fabric
• Work with Dataflows, Notebooks, and Lakehouse/Warehouse
• Model data for analytical consumption (star schema)
• Create and maintain dashboards and reports in Power BI
• Develop metrics and KPIs
• Integrate different data sources (APIs, SQL databases, files)
• Optimize query and model performance
(DBA – secondary role):
• Create and optimize indexes in SQL databases
• Support basic database maintenance
• Monitor performance and suggest simple improvements
• Support troubleshooting of slow queries
Required qualifications
• Experience with Microsoft Fabric (or equivalent such as Azure Synapse)
• Experience in data engineering
• Proficiency in Power BI (DAX, modeling, and visualization)
• Advanced knowledge of SQL
• Experience building data pipelines
• Knowledge in analytical data modeling
+ Basic/intermediate DBA knowledge:
• Creation and use of indexes
• Understanding of SQL performance tuning
• Basic knowledge of database maintenance (queries, locks, etc.)
Differentials:
• Experience with Azure (Data Factory, Data Lake, Synapse)
• Knowledge in Python or Spark
• Experience with Power BI Service
• Knowledge in data governance
• Experience with large data volumes
Desired profile
• Analytical and structured profile
• Good communication with business areas
• Proactivity and autonomy
• Ability to solve end-to-end problems
• Attention to performance and data quality
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