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Senior Data Analytics Lead (SAS / AWS) - Banking 12 month FTC

Employer
EXL
Location
UK
Salary
Competitive
Closing date
23 Feb 2021

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Sector
Technology & New Media
Contract Type
Permanent
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Job Details

EXL Service is a fast growing operations management and analytics firm. We are focused on growing our analytics business here in the UK, with a particular focus on our UK banking clients. We are looking for a highly motivated data architect to join our growing team.

Help us improve our client's customer and risk data management by bring your technical data architecture expertise. We are offering a role which will enable a strong data architect to grow client facing and business consulting skills in a fast paced environment.

This is an initial 12 month FTC with benefits

Role objectives

Achieve excellence in data delivery consulting engagements

Delivery

· Take lead and "hands on" data analytics and engineering consulting engagements (Leading teams of 1 - 5)

· Develop and execute programme / project delivery plans for implementation of solutions

· Understand how people, process, technology and data work in concert forming operating models to enable data delivery and science teams

· Assist to identify opportunities for sales opportunities during consulting engagements

Data architecture and engineering

· Stay abreast of technology products / services in the data and analytics space

· Advise delivery teams how best to deploy solutions

· Develop working prototypes in labs

· Develop white papers and other thought leadership

· Play a key role in build the team (recruitment of the role holder's direct reports)

Key Skills:

Technology and methodologies

· Cloud implementation of data solutions (AWS, Azure)

· Analytics tools (SAS, Tableau, Python)

· Graph and No-SQL databases (MongoDB, etc)



Delivery

· Project and programme management (PRINCE, PMI, other)

· Architecture and implementation (DCAM, TOGRAF, other)

· Service Management (ITIL, COBIT, other)

· Influencing skills (managing client and leadership in technical decisions)

· Explaining very technical topics to non-technical audiences

Data models

· Relational, graph and semantic data modelling (appreciation for all, with deep knowledge in one)

· Relational data base and warehouse design

· Information flow analysis (requirements, KRIs/KPIs, DQ controls, etc)

· FIBO (Financial Information Business Ontology)

Industry

· Retail, commercial or investment banking experience essential

· Appreciation of Financial Services / banking risk management frameworks and compliance needs (e.g. BCBS239, GDPR, Resilience)

· Appreciation for risk data architecture (credit, operational, compliance, etc)
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