Data Engineer

roject context

We are seeking data engineering expertise to enhance our Monitoring Solutions product, which provides comprehensive monitoring capabilities for application performance, LOG events, and BAU KPIs. In alignment with the group’s initiatives to elevate service quality, we are developing several Quality of Service (QoS) dashboards using an industrial approach.

The data engineering service will involve constructing data pipelines with PySpark, developing tabular cubes using Analysis Services (DAX), and creating dashboards with Power BI.

The service will also include assessing needs to establish functional and technical requirements, supporting coordination with third-party teams such as the Data Integration and Datalake teams, and implementing data ingestion and transformation processes. Additionally, the service will involve implementing specific calculations and filtering based on requirements, as well as security and access control measures.

We are looking for expertise in data engineering and dashboard development to achieve the following goals and deliverables:

Design a technical solution that addresses our needs, including data modeling, integration flow, and data mapping.
Build an integration layer based on Azure Datalake using DAX, PySpark, Databricks, Azure Analysis Services, and Azure DevOps.
Develop Power BI dashboards connected to Azure Cubes.
Implement specific calculations as required.
We require a minimum of 2 years of expertise in the relevant tools, with a MANDATORY hands-on experience in Databricks, Azure Analysis Services, and Power BI.

We are open to levels of expertise: intermediate, advanced, and expert.