My client, a data specialist consultancy, is seeking a SAS Lead Consultant with strong SAS experience and an knowledge of the market / credit risk.
This is a permanent position working with top tier retail/investment banking end clients in London or Milton Keynes.
- The SAS Lead is a Team Leader who owns the delivery of the project’s business requirements.
- Project Managing smaller engagements without supervision
- Supporting the Program/Project Manager on larger projects in putting together proposals, business and functional specifications and project plans
- Conducting Feasibility Studies alongside Managing Consultants
- Managing the technical team members delivering the solution
- Owning the overall design and implementation of the project application software
- As required, adopting the role of a Technical Architect to ensure that the solution design is compatible with the overall system architecture and seeking feedback on the design from other team members. On the technical architecture side, the SAS Lead will be talking to business and technical stakeholders to understand the current SAS architecture and to propose a new, streamlined architecture that meets the client’s long term needs.
- Working closely with Data Architects to ensure that the design of the solution and the data architecture work together efficiently proactively identifying potential issues
- On the reporting and modelling side, the SAS Lead will work with the business and with data owners to define and model new dashboards and data marts.
- Working with the customer business users to ensure that the design of the solution accurately maps to the customer’s business requirements
- Identifying project risks / escalating issues and feeding back information to Managing Consultants, Project Managers, and/or Senior Management.
The Principal Consultant should also contribute to the continued success of my client by:
- Promoting and developing Consulting Services to clients by performing the role of Principal Consultant
- Providing creative source of ideas/solutions to address customer problems
- Enhancing individual, team and client knowledge
- Minimum 10+ years of SAS skills ideally within financial services organisations or consulting/software firms serving this sector.
- Knowledge in Financial Services - Credit Risk and Market Risk knowledge is particularly sought after. Gained either working in the business line function or by consulting/internal roles serving the area.
- Ability to provide technical and thought leadership in various focus areas, such as Data Warehousing, Analytics, Big Data, Risk and Finance.
- Good communication abilities - verbal and written
- Team Leadership skills
- The candidate will have delivered SAS software - including ETL, integration, and governance functions into large scale organisations and understand the complexity of delivery.
- Candidates will have skillsets in project management and data governance.
- Ability to qualify and analyse clients or partners’ requirements and ability to map solutions to these requirements
- Strong SAS base, including programming and macros
- SAS Enterprise Guide
- SAS practices and governance
- Strong experience of Information Management implementation practices
- Good understanding of Warehousing and methodologies i.e. Kimball, Inmon, optimization, data integration, cubes and reporting.
- Knowledge of server operating systems (Windows and UNIX, Solaris, AIX and/or HPUX)
- High level database design expertise in major Relational Data Management Systems (e.g. Oracle, SQL Server)
- Knowledge of web technologies (HTML, XML), application server environments (ASP, JSP, JAVA, .Net) and web servers (IIS, Apache)
- SAS modelling
- Dashboard / report design
- Data quality / MDM
- Knowledge in some of the following:
- Applications Reporting
- Data Management and Governance
- Complex Architecture and Deployment
- Information Management
- Analytical Applications
- Web Services
- Sizing & Volume testing
- Version upgrades
- Agile development methodologies
- Big Data
- Credit Risk
- Market Risk
- Agile Methodologies
- Big Data
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