Junior Data Analyst

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 functions

Skills 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.