Junior Data Analyst

Role overview An early-career analytics role embedded in a Marketing Analytics team, focused on turning large marketing datasets into actionable insights and automated workflows. The work blends SQL and Python analysis, cloud data engineering on Databricks, and hands-on use of AI-assisted development tools to build agentic layers over the data pipeline. It suits a quantitatively trained graduate with prior internship or project experience who wants to learn fast on real business data.

Responsibilities - Analyse marketing performance data to surface trends, optimisation opportunities, and key acquisition and conversion drivers. - Design and build an intelligent lead ingestion framework that automates import, AI-driven parsing, validation, and enrichment of incoming leads. - Write efficient SQL queries to extract, transform, and analyse marketing and enterprise data. - Use Python for data cleaning, automation, and exploratory analysis, and assist in maintaining curated datasets and data quality rules. - Use AI-assisted development tooling to design interfaces, agents, and automation steps within the analytics stack. - Develop and maintain dashboards and recurring performance reports, and partner with marketing, data science, and data engineering teams. - Document data definitions, logic, and reporting methodologies.

Requirements - Strong working knowledge of SQL, including joins, aggregations, and data transformations. - Basic to intermediate proficiency in Python, with exposure to libraries such as pandas and NumPy through coursework, projects, or internships. - Familiarity with Databricks, Apache Spark, or comparable cloud-based data environments. - Bachelor's degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or a related quantitative field. - Internship, academic project, or research experience involving data analysis. - Analytical rigour, attention to detail, and the ability to explain technical findings to non-technical audiences.

Nice to have - Experience with Tableau, Power BI, or similar visualisation tools. - Familiarity with marketing analytics concepts or campaign performance metrics. - Exposure to marketing platforms such as Google Analytics or Salesforce. - Comfort with Git or other version control tools, and a basic understanding of ETL or data pipeline concepts.

Benefits and work setup - 25 paid vacation days, plus 4 additional global well-being days and 24 paid volunteer hours per year. - Private medical, dental, and vision insurance with dependent enrolment options. - Life insurance, income protection after 26 weeks, and a defined contribution pension plan with employer match. - Worldwide travel insurance and an Employee Assistance Programme with therapy, legal, and financial support. - Structured learning via on-demand libraries, mentoring, workshops, and an annual global learning day. - Access to AI-assisted development tooling as part of the daily workflow.