Data Manager (F/M) – Stockholm, Sweden

Job Type(s): CDI Freelance
Location(s): Stockholm
Company Name: infeurope S.A.

Infeurope is looking for a Data Manager (F/M) based in Stockholm.

Tasks:
• Support routine and ad hoc data collections from EU/EEA Member States, neighboring countries and other external or internal sources;
• Define, prepare, execute and test data migrations and transformations (historical data migration);
• Ensure proper data governance, integration and storage by maintaining and further developing the surveillance data warehouse and automated data flows;
• Assist data providers with their data preparation, submission and quality issues;
• Ensure data quality is properly defined, documented, analysed and monitored;
• Support the company’s experts as well as external requestors by preparing quality datasets according to the requirements;
• Support data analysis and visualisation in close collaboration with the client’s staff, such as disease surveillance experts and fellow data managers;
• Support relevant IT projects by ensuring that data-related requirements are properly defined and implemented;
• Any other tasks related to his/her area of work as requested.

Minimum requirements:
• University degree with at least 3 years of experience in data management OR non-university degree with at least 5 years of experience in data management;
• During the past five years: At least three years of experience in handling large, complex data sets using SQL;
o At least three years of experience in data quality assurance, including data quality analysis and data validation;
o At least two years of experience using MS SQL Server;
• Level of English, both written and spoken corresponding to CEFR level equal to B2 or higher.

Advantageous experience (at least 6 months during the past five years):
• Data management in infectious diseases, epidemiology or public health;
• Provision of external user support through helpdesk;
• Data warehousing (modelling, loading, tuning);
• ETL tools to create and manage data flows, data migration, data manipulation and aggregation;
• Data manipulation using R, Python, or similar;
• Work in a multicultural context

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