Job Details

Operations Data Analyst

Pharmacy2U

Overview

Do you want to work for the nation’s largest online pharmacy ensuring excellence for all our patients?
£35,000 to £45,000
per year
Full time, Permanent, Hybrid
(37.5 hours per week, Monday to Friday. We work on a core hours principle. Our core hours are 9:30am to 4pm, you can work around these to suit you!)
Leeds, LS15 8GB, We operate a hybrid schedule, meaning 2-3 days a week in the office based at Thorpe Park, Leeds

Key information

We’re a market leader in the pharmacy world, with 25 years’ experience, helping over 1.6 million patients in England manage their NHS prescriptions from request through to delivery.  We are Great Place to Work certified as we consider colleague experience a top priority every day.  

About the role

We are seeking a highly motivated Data Analyst to join our operations data team. In this role, you will be focusing on creating and maintaining a reporting suite focusing on Operational areas of our business. This role will play a crucial part in analysing and interpreting data across multiple sites and working with multiple teams.

This role involves leveraging data to provide insights that drives operational decisions, optimise warehouse processes, enhances customer experiences, and improve overall business performance. The Data Analyst will collaborate closely with cross-functional teams, including purchasing, clinical, and operations to support each team’s objectives.

Requirements

Who are we looking for?

  • Bachelor’s or master’s degree in a related field
  • Expertise in Power and SQL, and other data visualisation and reporting tools (Tableau and Looker)
  • Experience building and maintaining automated dashboards and reports in Power BI, Tableau, or Looker
  • Hands-on experience using SQL for data extraction, transformation, and analysis
  • Experience with data modelling and creating reusable data pipelines for reporting
  • Experience analysing large and complex datasets to identify operational inefficiencies or business opportunities
  • Prior involvement in developing forecasting models (for example, demand forecasting, workload capacity planning)
  • Experience measuring and improving key performance indicators (KPIs) related to service levels, accuracy, and turnaround times
  • Involvement in root cause analysis for operational issues and recommending corrective actions

We will be interviewing for this role as suitable applications are received and may close this role before the closing date upon a successful candidate being appointed.