Junior Data Quality Analyst

As a Junior Data Quality Analyst, you will play a crucial role in safeguarding the accuracy, completeness, and reliability of Kpler’s global commodity market data, with a primary focus on Oil Market Data. Working cross-functionally across business units, you will monitor data health metrics, identify system anomalies, and build actionable dashboards that empower decision-makers. In this role, you will also help pioneer internal workflow automation by experimenting with modern AI-driven tools to streamline data validation and analysis

Key Responsibilities

• Monitor and safeguard data integrity: Track data quality KPIs across multiple systems to detect inconsistencies, anomalies, and gaps, escalating critical issues to protect global commodity data reliability.
• Build intuitive visual analytics: Design, deploy, and maintain dynamic BI dashboards and reports to present clear data health insights to key stakeholders.
• Perform exploratory analysis: Utilize SQL and BI software to investigate datasets, discover underlying patterns, and resolve complex data quality challenges.
• Drive process automation & AI integration: Streamline data validation workflows by leveraging automation tools, prompt engineering, and modern AI techniques.
• Collaborate cross-functionally: Partner closely with Data Operations, Business Unit Engineers, Data Engineers, and BI teams to align data quality standards with business needs.
• Conduct root-cause investigations: Address ad-hoc stakeholder inquiries and deliver swift, accurate data analysis to support operational decision-making

Experience & Background

• 1-2 years of hands-on experience in a data-focused role or internship (e.g., Data Analysis, BI, or Data Science).
• Bachelor’s degree (or higher) in a quantitative field such as Economics, Computer Science, Statistics, Business, or equivalent practical experience.
• Solid foundational SQL skills with the ability to query, filter, aggregate, and join complex tables efficiently.
• Practical familiarity with Python, GitHub, and spreadsheet tools (Excel or Google Sheets) for data manipulation and profiling.
• Working experience with modern BI visualisation tools such as Looker, Tableau, or Power BI.
• Meticulous attention to detail, strong problem-solving skills, and a desire to take end-to-end ownership of data accuracy.

Nice-to-haves:

• Exposure to or strong interest in energy, commodities, or Oil & Gas markets.
• Active interest in AI tools and best practices, with a focus on improving documentation, streamlining workflows, and enhancing quality assurance processes.