Data Analyst – Financial Services Job Description Template
Our company is looking for a Data Analyst – Financial Services to join our team.
- Help Clients understand the best mix of technologies, solutions and services, and how to deliver them to maximise business value;
- Work and collaborate with various offshore and 3rd party suppliers, adapting your communications approach to meet the business demands;
- Organise meetings and take notes of all of the analysis;
- Understand problems and issues in the current architecture;
- Act as the interface between data architects, SME and content experts;
- Analysis to identify data requirements, attributes, entities and relationships, gather data dictionary definitions;
- Work closely with SME’s and data architects;
- Analyse the actual data itself.
- Excellent interpersonal, communication and client management skills;
- Organise and facilitate meetings & workshops and record actions and decisions;
- Understanding of RDBMS’s and proficiency with SQL;
- Prior experience with least 5 years having worked on large data migration programmes;
- Full lifecycle experience from project inception, feasibility, design – through to project delivery;
- Desire to keep learning about new practices and technology, supporting EPAM’s Software Engineering Excellence;
- Exposure and understanding of different agile approaches and good working knowledge of analysis tools including Jira;
- Understanding of JSON, XML & Semantic Web technologies (e.g. RDF, OWL, SPARQL & SHACL) desirable but not essential;
- Stakeholder Management experience and skills – able to converse with all levels of stakeholders to understand and extract requirements;
- Working with nearshore developers, understanding the challenges of working in a nearshore delivery model;
- Experience of working in a sales environment, which also includes the ability to sell ideas internally;
- Experience of Sparx Systems Enterprise Architect desirable but not essential;
- Good understanding of financial reference and/or market reference data;
- Understanding of UML and or logical data models is essential for this role.