Lead AI, MLOps & Data Engineer at WedR, guiding complex data projects and AI innovation. Collaborate with diverse experts in a Product Studio for digital transformations.
About the role
- 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.
Benefits
- Health insurance
- Paid time off
- Professional development opportunities
- Flexible working hours
- Remote work options
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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