Overview
Business Analyst- Data Modelling & Data Analytics- Finance Domain Jobs in Geneva, Switzerland at Ampstek
Title: Business Analyst- Data Modelling & Data Analytics- Finance Domain
Company: Ampstek
Location: Geneva, Switzerland
Job Description:
- Mandatory practical experience in Finance (Must have), Wealth Management and Private Assets (desired) as business analyst, business engineer or requirements engineer
- Advanced capabilities in SQL, XLS (DBT and Python are a plus)
- Advanced knowledge in Data Modelling and Data Analytics (E.g. Power BI, Tableau)
- Collaborative mindset – Have proven experience where his/her capacity to foster collaboration has made a strong difference
- Relevant practical experience working with agile framework
- Experience of SaaS business solution integration is a plus, in particular in Alternative Investment.
- Rigorous and analytical mindset
- Passion for continuous improvements. Not satisfied with the status quo and always thinking of ways to improve
- An intuitive eye for customer needs beyond the obvious
- Excellent attention to details
- Very good communicator
- Resistance to pressure and changing environment
Responsibilities
- Provide functional and technical support for agile IT projects in the financial and banking sector across the entire project lifecycle.
- Capture and translate business requirements using requirements engineering and modelling techniques, covering the full data lifecycle.
- Collaborate with internal and external stakeholders to design and develop effective data solutions.
- Ensure timely delivery, quality, and long term maintainability of Data Products.
- Manage an entire business line: from needs collection and prioritization to delivery coordination with Data Engineers and final stakeholder handover.
- Contribute to internal initiatives and proactively bring new ideas to enhance professional, methodological, and organizational practices.
- Define business test cases to support Data Engineers in validating functional features and preparing data quality assessments.
- Strong understanding of Data Products, Data Ownership, and Data Governance principles.
