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Data Analyst

Capgemini

Capgemini

IT, Data Science
Malaysia
Posted 6+ months ago

Responsibilities:

  • Ensure data to be organized, structured, and represented in a way that supports efficient data management, analysis, and reporting.
  • Design, implement and maintain data models for Finance Data Repository (FDR), required to deliver on the Proof of Vallue (PoV) and future state FDR business use case Support IT Delivery team for FDR build – including logical data model design, transformation logic, data quality logic within frameworks.
  • Responsible in develop and maintain entity-relationship diagrams (ERDs) to represent data entities, relationships, and attributes.
  • Collaborate with cross-functional teams to understand data requirements and provide technical advice Conduct data profiling and ensure data quality analysis is compliant with l framework and standard practice.
  • Ensure data security, compliance, and governance standards are met In-depth knowledge of the principles and practices of good systems design Qualifications

Experience & Skills:

  • Bachelor’s degree in a relevant field advanced degree preferred.
  • Proven experience in delivering enterprise data platform projects.
  • Proficiency in data modelling techniques, including conceptual, logical, and physical modelling and knowledge of industry standards and best practices in data modelling and database design Strong understanding of relational database management systems (RDBMS) such as PostgreSQL, MySQL, Oracle, etc.Mandatory skills
  • Expertise in finance data modelling techniques, database design principles, and proficiency in database management systems and test automation Strong background creating entity-relationship diagrams, dimensional models, and other modelling artifacts to represent complex data structures.
  • Proficient in SQL for querying and manipulating data.
  • Experience in designing financial data marts to support business intelligence use case
  • Experience in Agile and DevSecOps delivery, quality practices, techniques and tools required for all aspect of data engineering/ data platforms.
  • Experience with cloud-based technologies incl. Microsoft Azure, Azure Data Lake, ADLS, Databricks, Delta Lake Experience with JIRA, Confluence, Github, Bitbucket and other similar developer tools.