Data Engineer (Finance Data Foundation)

This is a remote position.

We are looking for someone to support the implementation of the new Finance Data Foundation platform by building and migrating semantic models, data pipelines and reporting capabilities that replace the current Azure Analysis Services solution.

Key Responsibilities:

· Build and maintain data pipelines and data models.

· Implement semantic models using Cube.js/Cube Cloud.

· Support migration from Azure Analysis Services.

· Develop solutions using SQL, Python and Databricks.

· Optimize performance and scalability of analytics workloads.

· Collaborate with Finance stakeholders on KPI definitions and reporting requirements.

· Support data quality, governance and metadata initiatives.

· Contribute to architecture and design discussions.

Required Skills:

· Strong SQL

· Python

· Databricks

· Data Modelling

· Data Warehousing / Lakehouse

· Cube.js or similar semantic layer technologies

· Azure Analysis Services, SSAS or equivalent OLAP technologies

· Report and semantic model migration experience

Nice to Have:

· Finance or EPM domain experience

· KPI governance

· Data catalog and metadata management

· Power BI

Required skills

· Databricks

· SQL

· Python

· Azure Analysis Services

· Data Warehousing