Senior Data Analyst (Companies/Ownership)
Reads like a Data Governance role: data quality and governance.
Greece
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingOwn end-to-end quality of vessel particulars datasets, including ownership and classification
Research and validate vessel data from multiple sources
Find data gaps and anomalies, and build validation checks
Create SQL and Python workflows to automate data collection and cleansing
Investigate and fix data quality issues raised by internal teams or customers
From the employer’s posting
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.
Investigate and resolve data quality issues raised by internal teams or customers, identifying root causes and implementing fixes.
Tools in this posting
- Python
- SQL
Source — Tool mentions in context
- 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.
- 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.
- 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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 16, 2026 · 15 days ago
- Recorded sightings
- 21
- Last seen by us
- Nov 1, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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.
Employment type
Full-time
Source details
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- Pay
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- Location & working pattern
Greece
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- Work authorization
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