The Junior Data Analyst will work alongside senior analysts and engineers across the full BI lifecycle from supporting data pipeline quality checks, to building and maintaining dashboards in Looker, to helping commercial and operational stakeholders make sense of their data. There is no fixed lane: you will be exposed to the breadth of what a modern BI team does in a fast-moving B2B SaaS environment, giving you the foundations to develop into a well-rounded data professional.
Key Responsibilities
Assist in building and maintaining dashboards and reports in Looker, ensuring they are accurate, up to date, and easy to interpret by non-technical stakeholders.Support senior analysts in translating business questions into SQL queries and data models, progressively taking on more ownership as your skills grow.Help maintain and document the LookML codebase, including updating fields, and flagging inconsistencies.Run data quality checks across key datasets and flag anomalies or discrepancies to the team.Contribute to the team’s data dictionary and technical documentation, ensuring definitions are clear, consistent, and accessible to all stakeholders.Support testing and validation of new data pipelines and transformations before they go to production.Engage with internal stakeholders (commercial, finance, operations) to understand their reporting needs and communicate progress clearly.Help prepare data-driven summaries and ad-hoc analyses to support business decisions.Act as a bridge between the BI team and less data-literate audiences, helping them interpret and use data confidently.Actively participate in team rituals, standups, code reviews, retrospectives and bring a collaborative, solutions-oriented mindset.Proactively seek feedback and apply it; treat every task as a learning opportunity.Stay curious about Kpler’s data, products, and the commodity trading industry. The more context you build, the more valuable your analytical contributions become.Collaborate across Sales, Customer Success, Marketing, Product, Finance, RevOps and SalesOps functionsSkills and Experience
1-2 years of experience in a data-related role or internship (BI, data analysis, data science, or similar).Working knowledge of SQL. You can write queries, filter, aggregate, and join tables. You’re not expected to be an expert, but you’re comfortable enough to learn fast.Exposure to a BI or data visualisation tool (Looker, Tableau, Power BI, or similar)Familiarity with spreadsheets (Excel or Google Sheets) and a general comfort with data manipulation.Mindset & Soft skills
Intellectual curiosity: you don’t just complete tasks, you ask questions, explore data, and want to understand the “why” behind the numbers.We're a team that actively experiments with AI to move faster and think sharper. If you're curious about how AI tools can augment analytical work, you'll feel right at home.Attention to detail: you care about accuracy and take pride in producing work that others can trust.Structured communicator: you can present your findings clearly, adapting your language depending on whether you’re talking to an engineer or a commercial director.Growth mindset: you actively seek feedback, embrace challenges, and see setbacks as learning opportunities rather than failures.Ownership mentality: you take initiative, follow through on commitments, and don’t wait to be told what to do next.Team player: you thrive in collaborative environments, are generous with your knowledge, and make the people around you better.Adaptability: you’re comfortable with ambiguity and can prioritise and re-prioritise in a fast-paced, evolving environment.Nice to have
A bachelor’s degree in a quantitative or analytical discipline (Economics, Business, Computer Science, Statistics, etc.) is appreciated.Any experience with Python, dbt, or version control (GitHub) is a bonus, not a prerequisite.Additional
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