Senior Data Analyst (Companies/Ownership)

Job description

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 Senior Data Analyst within our Data Platform team, you will be the subject matter expert behind Kpler’s company and ownership datasets. You will be responsible for ensuring the accuracy, structure and ongoing development of company-level data, including ownership, management, operator and corporate hierarchy information. Your deep understanding of the maritime industry and its corporate landscape will help establish a reliable source of truth for asset ownership, supporting our wider data platform strategy and enabling other datasets, products and teams to build on consistent, trusted information. Starting with maritime companies, you will help expand our coverage over time to include other asset classes and related industries, such as ports, terminals, refineries, commodities and infrastructure. You will use your industry judgement to lead complex data investigations, identify gaps and drive improvements in data quality and coverage with a high degree of independence. While technical data skills are important, this role places particular emphasis on your industry expertise and ability to translate complex ownership structures into clear business rules and reliable data models. You will also collaborate closely with Product, Engineering, Market Analysts and other Data Analysts to strengthen our data capabilities and support commercial and customer-facing teams. ### Responsibilities - Own the end-to-end quality of assigned vessel particulars datasets, including specifications, ownership, classification and technical attributes. - Research and validate vessel data from multiple sources, ensuring accuracy, consistency and completeness. - Analyse datasets to identify data gaps and anomalies, developing and running validation checks to improve data quality and coverage. - Create and maintain SQL- and Python-based workflows to automate recurring data collection, cleansing and enrichment tasks. - Develop dashboards and reports to monitor vessel data quality, providing Market Analysts with relevant vessel-level insights. - Support the integration of new vessel data sources, including scoping, testing and validating incoming data feeds. - Investigate and resolve data quality issues raised by internal teams or customers, identifying root causes and implementing fixes. - Document data logic, business rules and definitions to ensure consistency and adherence to vessel particulars data standards. - Collaborate with Product and Engineering teams to translate data quality findings into platform and pipeline improvements. - Work proactively with the Vessel Data Manager, taking ownership of issues independently, communicating clearly and recommending solutions. ### Skills and Experience - 2–4 years of experience in a data analyst, data quality or data operations role. - Experience working with SQL for data querying, cleansing and analysis. - Demonstrable knowledge of vessel data and maritime shipping concepts. - Experience working with large, real-world datasets, particularly vessel particulars. - Experience in the maritime industry. - Strong analytical skills, with a structured and detail-oriented approach to problem-solving. - Experience with data validation, monitoring and quality-improvement techniques. - Strong ownership and accountability, with the ability to work independently and prioritise effectively. - Clear communication skills, with the ability to work effectively with technical and non-technical stakeholders. ### Nice to have - Familiarity with data visualisation tools and dashboarding. - Practical experience with ETL processes and/or web scraping for data collection. - Experience using Python for data analysis and automation. - Experience working with APIs for data ingestion and validation. - Experience building or maintaining data pipelines - Familiarity with maritime data sources.