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Associate Data Analyst

External
clarivate logoClarivate · R155-belgrade
Full-timeHybrid1w ago
Data AnalysisETLPythonSQL
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About the role

The team is distributed across Belgium and India, and in this role, you will report directly to the Manager, Solutions Analysis.

Benefits

Holidays: 25 days paid leave per annumPrivate Health InsurancePaid LunchYearly BonusYearly Merit PlanMy Learning PlatformFit PassLife InsuranceAccident InsuranceCompany bicycles for rent free of chargeHours of WorkThis is a permanent full-time position, with core engagement hours within CET time zone. This is a hybrid position; you will be expected to work from our Belgrade office 3 days every other week.Please note that only shortlisted candidates will be contacted.#LI-HybridHealth insurancePerformance bonus

Additional Information

We are looking for an Associate Data Analyst to join our team in Belgrade and support data-driven solutions within our IP segment, working on global trademark and brand protection products. In this role, you will gain hands-on experience with data pipelines, ETL processes, and textual data analysis. This is a great opportunity to build strong analytical skills and contribute to meaningful, real-world data projects. About you - experience, education, skills, and accomplishments Bachelor's degree and /or equivalent work experience Proficiency in English It would be great if you also had . . . 1 year of experience as a Data Analyst 1 year of experience with SQL, Python, PowerQuery or similar tools Exposure to ETL processes or data pipelines Previous experience with textual data What will you be doing in this role? Extract, validate, and transform textual data using SQL, Python, PowerQuery, or other querying tools. Coordinate with senior analysts and stakeholders to ensure the quality and accuracy of analytical outputs. Reverse engineer existing textual ETL systems. Create requirements for software engineering, specifying the data pipeline. Perform operational data tasks, i.e. adjustments of legacy data systems and corrective loads. Root cause analysis of data issues.

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