Data Warehouse Analyst

Mantu is an independent international consulting player, founded in 2007. Bringing together expert and complementary brands, Mantu stands out for the breadth of its spectrum, responding to all business transformation challenges.

Its activities are divided into four practices: Leadership & Advocacy, Technology, Digital Marketing & Experience, Total Talent Management. A wide range of skills, all serving a single mission: connecting and powering companies with leading teams and technology to succeed faster and sustainably.

From its headquarters in Geneva, Switzerland, Mantu relies on a community of 11,500 talented people in more than 60 countries on 5 continents and has a turnover of 1 billion euros.

Our values are our guiding principles that steer everything we do; from the way we work with our clients and partners to how we interact with our teammates and candidates. The Mantu values – Pioneer Spirit, Care, Trust, Performance, and Independence as a cornerstone – are equally important and reflect our purpose: we are in business to build the next generation of sustainable pioneers.

Your profile

• At least 3 years of experience in a similar role;

• Advanced knowledge of products/services in the banking system, previous experience in a similar position;

• Advanced SQL knowledge and experience in transactional and operational modeling techniques, analytical and MDM;

• Knowledge of structured data, such as entities, classes, hierarchies, relationships and metadata;

• Knowledge of the physical implementation of database management systems (DBMS), including tables, joins and SQL queries;

• Experience in Teradata technology is an advantage;

• Proficiency in English.

Your role will include tasks like:

• Analyzing business requirements and creating functional specifications as a guide for data modeling;

• Involvement in defining and identifying validation solutions for the consistency of the reported information, in defining and implementing the corresponding processes and in qualifying the data quality defects identified;

• Unifying multiple logical data models from source systems into a secure, logically consistent one;

• Rationalizing the relationships expressed in the logical data model in the schematic of the physical data model (tables and columns);

• Mapping business terms from source systems into the DWH Core model;

• Performing design activities and proposes new tables and relationships in Data Marts;

• Drawing up the development documents, according to the approved standards, completing the sections of which he responds as an analyst, in collaboration with the other teams;

• Being responsible for UAT support.