Junior Data Quality Analyst

LondonHybridFull-time

AI Summary

Monitors and safeguards the accuracy and reliability of commodity market data, primarily oil market data, by tracking data quality KPIs, investigating anomalies, and building BI dashboards. Also helps automate data validation workflows using AI-driven tools.

About this role

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.

Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.

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.

Skills

Dashboard DesignData Quality MonitoringExcelExploratory Data AnalysisGitHubGoogle SheetsLookerPower BIPrompt EngineeringPythonRoot-cause AnalysisSQLTableauWorkflow Automation

Junior Data Quality Analyst

About this role

Key Responsibilities

Experience & Background

Skills

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