Data Analist Utrecht • Experis

Vacatureomschrijving

You will enter a challenging environment where they work according to Agile/Scrum/DevOps methodologies. You main tasks involve:

• You will implement Data Lineage.
• You will engage in Reference Data Management
• You will perform changes in Logical Data Models as per the requests received from the other stakeholders.  
• You will implement data governance
• You will perform data quality validations. 
• You will identify underlying data issues.
• You will review data definitions that are used by different business units.

Functie-eisen

• You have a Bachelor’s Degree
• You have a minimum of 4 years of experience working with Data.
• You have knowledge and experience using SQL (i.e. how to write a basic select query and an adjoint query)
• You have knowledge and experience working with Databases like Oracle.  
• You have experience working with Data Quality and an understanding why is it important.
• You have worked on Data Governance with tools such as Collibra.
• Having relevant financial experience is preferred.
• Knowledge of PowerBI, Python or Business Objects is preferred.
• You have strong communication in English, spoken and written.

Aanbod

Arbeidsvoorwaarden

• Holiday pay 8% of gross annual salary;
• 25 Vacation days + 0.5 bonus day per 6 months if you have remained fit and healthy (read: do not report sick);
• Travel allowance 19 cents / kilometer;

Sollicitatieprocedure
For more information please contact Michelle Morsink via de button "Solliciteer nu" op deze pagina. or call 0031643230617.

Bedrijfsomschrijving

You will work in a large financial organization in the Netherlands. The department consists of 15 people, which are divided into two teams of around 7 to 9 members. Each team focuses on different regions of the world. The team is responsible for carrying out data usage, besides understanding the architecture and backbone of the data. The department acts as a bridge between the stakeholders within the Finance, Risk and IT domains. The team works with both financial and non-financial data, for example loan financing data and understanding how a customer get its ID.