Connecting to LinkedIn...

Data Manager

Job Title: Data Manager
Contract Type: Permanent
Location: London, London
Industry:
Salary: £40000 - £50000 per annum
Start Date: ASAP
REF: 0610
Contact Name: Zoe Hallam
Contact Email: zoe.hallam@parallelconsulting.com
Job Published: 10 months ago

Job Description

An exciting opportunity to join a leading provider of valuation Model technology in their high end offices in London. Delivering products and services to support critical decision making and risk management across the mortgage and residential markets. Dealing with high profile clients within the public sector, real estate sectors, developers, capital markets and real estate professionals. This is an excellent opportunity to join an expanding team, in a role that provides you a clear cut route to your career progression.

Responsibilities:
You will play a central role in planning and managing the data in the most efficient way. Working with senior stakeholders on new product development and alongside Data Engineers in the team to get a deep understanding of their ETL processes and Data Warehouse structures.

Essential Skills Required:
- Experience of working with SQL (in particular T-SQL)
- Advanced Excel Skills
- Knowledge of ETL processes
- Experience in Data Querying, Profiling & Manipulation
- 3+ Years' experience in a similar role

Desirable Skills:
- An understanding of a relational database (RDBMS) schema design
- Educated to a degree level or equivalent
- Knowledge of GIS data will be an advantage

This leading client not only offers a great salary, far outweighing those of similar companies, but also offers a very comprehensive benefits scheme including; 25 days holiday, free gym membership, life insurance up to 4 times your salary and heavily discounted medical insurance - Plus many more benefits!

Parallel Consulting is a multi-awarding winning, global leader in Analytics & Data Science recruitment.
With over 12 years expertise, we assist our clients within Analytics, Customer & Marketing Insight, Web Analytics, Big Data, Data Science, Credit Risk and BI.