Our Client is looking for a Data Engineer, who's key objective is to design and build out a global, stable and up-to-date data warehouse functionality that can fulfil the needs of portfolio managers, data scientists and analysts. Therefore, this platform requires setup and integration of multiple internal and external data sources, building a data catalogue and ensuring that data ownership and data completeness are in place

1. Build and ongoing review of functional and solution design of a data lake.
2. Develop Databricks notebooks for data delivery and Datamodelling as well as SQL scripts
3. Translate functional requirements into technical specs supported by a business analyst.
4. Technical design and build of interfaces and data feeds using Informatica and/or Azure technologies.
5. Create and maintain appropriate documentation using existing tools such as Jira/Confluence and applying Company's standards.
6. Ensure collection of meaningful data and feedback across the whole organization, while engaging stakeholders into the importance of a Data Layer
7. Ensure alignment with Enterprise architecture and Enterprise Data Office for all interface solutions.
8. Analyze and understand business processes and requirements, design IT solutions based on the analysis, assist business and IT-department during the implementation phase.
9. Design test planning as well as automated and manual management and execution. Document and execute functional test plans. Work with the end-user community to support the documentation and execution of UAT test cases.
10. Apply agile project and design methodologies

Onboard new datasets onto the central platform using Microsoft Azure stack (Azure Data factory, Azure Databricks)
1. Implement dimensional modelling based on the design provided using Azure stack
2. Conduct data demand analysis to ensure that all standards are fulfilled
3. Document the pipelines in Wiki

Overall Project Deliverables:
1. Data model and related data base structure.
2. Delivery of data migration activities, data onboarding and design required plans (eg migration, testing, data collection)
3. Review test cases and test execution and provide feedback for improvement.
4. Defect analysis and resolution based on provided information, infrastructure and tools.

Key Requirements:
Track record of project including Python and SQL
Previous experience or good understanding/capabilities of Cloud services (ie Microsoft Azure (Data Factory, Databricks, Data Lake)
Knowledge and experience of Asset Management industry is a plus