System Analyst at Barclays Bank PLC
Northampton, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

16 Sep, 25

Salary

0.0

Posted On

17 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Presentation Skills, Communication Skills

Industry

Information Technology/IT

Description

Embark on a transformative journey as a Data Analyst, at Barclays, where our vision is clear, to redefine the future of banking and help craft innovative solutions. Join us as a Data Analyst, where you’ll play a key role in driving governance, process improvement and agile transformation across the Insurance & Packs Sub-LAB within the Life Moments LAB.

To be successful as a System Analyst, you should have:

  • Change and Transformation including Agile Methodology & and adherence to change delivery controls.
  • Experience of engaging with stakeholders, hosting forums/ meetings to gather business requirements and create action plans of the back of those requests.
  • Data analysis and reporting, including Jira/JQL Reporting, taxonomy, Navigator/Tableau reporting.

Other highly valued skills include:

  • Good communication skills.
  • Presentation skills, ability to present data to a wide set of stakeholders.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
This role has the option to work from either the Knutsford or Northampton office.

ACCOUNTABILITIES

  • Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
  • Execution of data cleansing and transformation tasks to prepare data for analysis.
  • Designing and building data pipelines to automate data movement and processing.
  • Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
  • Documentation of data quality findings and recommendations for improvement.

How To Apply:

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Responsibilities

To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.

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