Business Data Analyst - Northampton, United Kingdom - Charles Jenson Recruitment Ltd

Charles Jenson Recruitment Ltd

Verified Company

Northampton, United Kingdom

2 weeks ago

Posted by:

Tom O´Connor

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Description

Hybrid - 3 days in office

Salary up to £50k

We need a Business Data Analyst that is passionate about data and able to use various methods to transform raw data into useful data systems.

The primary role of the Business Data Analyst is to combine expertise, programming skill, data science and businessintelligence to extract meaningful insights from the data.

This is a great opportunity has arisen for a Business Data Analyst, to work within a fast-growing technology company.
The role is hybrid, and the office is in Northamptonshire.

Your skills and experience

Experience as a Business Data Analyst or in a similar role ( for example Business Analyst, Analytics Engineer, Data Analyst or BI Developer).

Keyskills:

Strong analytic skills related to working with structured and unstructured datasets.
Highly organised critical thinker with a great attention to detail.
Exceptional communication and presentation skills in order to explain your work to people who don't understand the technical details.
Effective listening skills in order to understand the requirements of the business.
Strong problemsolving with an emphasis on product development, with the ability to come up with imaginative solutions.
Drive and the resilience to try new ideas if the first one doesn't work you'll be expected to work with mínimal supervision, so it's important that you're able to motivate yourself.
Collaborative approach and a 'gogetting' attitude, sharing ideas and finding solutions.
Accountable for the outcome, seeks opportunities and removes obstacles.
Strong planning, time management and organisational skills.
The ability to deliver under pressure and to tight deadlines.
A drive to learn and master new technologies and techniques.

Experience in and knowledge of:

Data warehousing and working with and creating data architectures.
Building and optimizing' big data' data pipelines, architectures and datasets.
Manipulating, processing and extracting value from large, disconnected datasets.
Build processes supporting data transformation, datastructures, metadata, dependency and workload management.
Datamodels, datamining, and segmentation techniques.
Using computer languages to manipulate data and draw insights from large data sets.
Developing and maintaining ETL/ELT routines.
BI tools.
A variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their realworld advantages/drawbacks.