Data Architect engaging in enterprise-level data architecture solutions for various data platforms and strategies. Focus on data capabilities to support business objectives.
Responsibilities
Gain an understanding of the various programmes that have data at the heart of them e.g. Data Lakehouse, Enterprise risking, Advanced Analytics, MI reporting and AI to provide a perspective on how these capabilities can be delivered through various project and programme solution designs, aligning to the data strategy.
Produce architectures and designs for complex end-to-end data solutions, including platform, ETL, Reporting, AI and Analytics
Provide advice to clients on architecture/infrastructure, platform and engineering best practices across Data Warehouse/Data Lake solutions and modelling concepts.
Take ownership of the client requirements, deliverables and accountabilities to ensure adherence to Architecture Governance processes, industry best practices and to maintain consistency with clients’ Architecture vision
Drive the solution development and documentation of solution designs ensuring good architectural practices are observed through the lifecycle of the solution development
Provide oversight of architectural direction for and on behalf of our clients
Develop excellent working relationships with our clients to become their trusted advisors through boldness and honesty
Manage relationships with vendors, third parties and the wider Capgemini
Ensure solution delivery is performed according to agreed specification while challenging the status quo, providing an alternative point of view as and when required.
Requirements
Good understanding of cloud native data services and offerings on both AWS and Azure
Experience with multiple data storage types and technologies in data warehouse and data lake solutions. Examples include relational DBMS (e.g. Oracle), Hadoop, NoSQL (e.g. Hbase), Columnar DBs (e.g .Amazon Redshift), Graph DBs (e.g. Neo4J), cloud object storage (e.g. Amazon S3), cloud DB as a service (e.g. Amazon RDS)
Understanding of architecture and design concepts for ETL/ELT solutions utilising a range of tooling (examples include AWS Glue, Azure Data factory, Talend, Pentaho DI, Informatica, SAS DI, Java)
Understanding of architecture and design concepts for data exploitation solutions and technologies includes Analytics (e.g. SAS, R), Reporting (e.g. Pentaho Business Analytics, Power BI) & APIs (e.g. Java, Denodo)
Demonstrable expertise in the areas of data modelling in large complex estates, implementation of multiple data architectures and integration of Data Management/Governance tooling
Experience in modern ways of working (examples include Agile, CI/CD, DevOps, Test Automation and utilising AI)
Experience working with On Premise, Cloud, and Hybrid solutions including Cloud Migration programmes.
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