As a Data Analyst at Prezzee, you will be responsible for gathering and interpreting data from across the business in order to support the organisation’s decision-making process and help achieve its broader strategic goals. You will identify patterns and trends in complex datasets, share insights and recommendations with senior stakeholders, and maintain the data infrastructure that forms our analytics stack.

This role will be instrumental in fulfilling our FY25 strategic ambition to disrupt the gift card and payments market globally

• Programming experience in Python and R
• Setting up and maintaining data pipelines - dbt and Talend Stitch
• SQL experience (we use Postgres 11.2 and AWS Redshift).
• Experience with Business Intelligence tools - Google Looker
• Marketing technology platforms - Twilio Segment and Google Analytics (GA4)
• Ability to analyse large datasets.
• Ability to write comprehensive reports.
• Strong verbal and written communication skills.
• An analytical mind and inclination for problem-solving.
• Attention to detail.
• Proficiency in data visualisation.
• Great understanding of spreadsheet tools (Microsoft Excel, Google Sheets).
• Advanced English communication skills (written and verbal)
• Be happy to coach, mentor and train less senior colleagues.

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General Responsibilities

• Reporting on key business metrics to stakeholders from across the organisation (Product, Strategy, Marketing and Customer Care, to name a few).
• Identifying and interpreting trends or patterns in complex data sets.
• Cleaning and normalising data from core business applications (e.g. Segment, Braze, the Prezzee back-end).
• Presenting data-driven findings and recommendations back to the business in a clear and actionable format.
• Working directly with management teams to gather requirements, scope and prioritise analytics work, and provide regular status updates.
• Engaging with business stakeholders to understand and document user journeys, in order to design and implement product feature analyses;
• Knowing the right questions to ask different stakeholders to get to the real problems to solve (which might not always be what they start with).

Technical Responsibilities

• Writing efficient, well-documented SQL code.
• Maintaining the infrastructure and tools that form our analytics stack.
• Creating and updating documentation for our analytics workflows and processes.
• Evaluating existing analytics processes for inefficiencies, problems, and inaccuracies, and identifying improvement opportunities.