
Senior Data Visualization Engineer
- Θεσσαλονίκη
- Μόνιμη
- Πλήρης Απασχόληση
- Generate business insights using distributed data sets to build reports, dashboards and visualizations using appropriate technologies.
- Manage data related contexts ranging across medium to large sized data sets, structured/unstructured or streaming data, extraction, transformation, curation, modelling for developing reports and dashboards to solve business problems and provide insights.
- Partner with data architects, data engineers and data analysts to design and build strategic Data Analytics & Visualization solutions.
- Work closely with data analysts, SMEs and stakeholders to understand the data, analysis needs, and outcomes; translate this understanding into effective BI, reporting and data visualizations solutions.
- Design and build robust data visualization solutions, with focus on automation, performance, resilience, scalability and security.
- Ensure the accuracy, consistency, and reliability of data visualizations by validating the data sources, implementing DQ controls and analyzing outcomes.
- Document data sources in enterprise data catalogue with metadata, lineage and classification information. Develop and maintain a library of dashboards, reports and related data visualization assets.
- Develop models and prototypes to provide observations, identify trends and patterns with leadership to assess potential solutions to business requirements.
- Provide training and ongoing support to business users in the use and interpretation of data visualizations.
- Actively participate and contribute to the Data & Analytics Community to create and enhance data visualization standards and best practices.
- Bachelor's degree (or equivalent) in Computer Science, Data Science, Information Systems, or a related discipline.
- At least 5 years of relevant hands-on experience in developing and executing effective data visualizations, dashboards, and reports, preferably in the insurance sector.
- Expertise in SQL and data visualization tools (such as PowerBI and Qliksense) and experience with statistical analysis tools and programming languages like Python is essential.
- Knowledge of data analysis methodologies and techniques, along with the ability to manage complex, large datasets.
- Practical experience with database systems, including cloud technologies (e.g., Azure, AWS) and RDBMSs (e.g., SQL Server, Snowflake).
- Familiarity with data extraction and transformation tools and platforms (e.g., Informatica, DataBricks).
- Demonstrated success in a collaborative, team-focused environment, ideally within a Scaled Agile framework.
- Fluent in written and spoken English.
- Excellent communication skills, capable of conveying complex information and data clearly to both technical and non-technical audiences. Knowledge of data storytelling techniques is also beneficial.
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