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Data Management Analyst

  • Location

    Reading

  • Sector:

    Data Analysts

  • Job type:

    Permanent

  • Salary:

    Market related

  • Contact:

    Kate Mangahis

  • Contact email:

    kate.mangahis@thebridgeit.com

  • Contact phone:

    07917 160 135

  • Job ref:

    3003KMA

  • Published:

    7 months ago

  • Expiry date:

    2022-08-24

Job Title: Data Management Analyst

Location: Remote + 2 days per month visit to Bracknell site (near Windsor)

Employment Type: Permanent

 

Job Description

A science-based agri-tech company is currently looking for a Data Management Analyst to join their UK team. They are global company, headquartered in Switzerland with sites across the UK. The successful candidate will be responsible defining data management requirements, whilst ensuring data quality is maintained.

 

Responsibilities

  • Governance of all data across the E business and wider organisation, ensuring that principles, policies, and controls are defined and validated.
  • Management of data quality and associated improvement activity to ensure that data quality is maintained at targets sets by the business.
  • Assurance that data, KPI, and reporting definitions, meanings, interpretation, and usage is aligned across the organisation and utilises best practice through the proactive driving of collaboration between organisational functions.
  • Driving the evaluation and enrichment of data via various sources (both internal and external).
  • Identification and assessment of data management and quality tools that are fit-for-purpose for use across the organisation, driving the procurement of the best tools, leading best practice research to evolve and maximise fulfilment of tool usage potential.

 

Requirements

  • Degree or relevant qualification / training in a Data Management or computer science discipline.
  • Knowledge and practical experience of Operational Excellence/LEAN Six Sigma.
  • Expert and demonstrable experience of Data Management and Data Quality documentation and implementation.
  • Experience and understanding of basic statistical analysis principles and techniques
  • Experience analytical science and associated data integration.
  • Strong planning and organisational skills.