finseats

Data Visualization Engineer

Chubb (Chubb) · Other

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  • 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 visualisation 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 analysing 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 visualisation 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 visualisation standards and best practices. 

  • Bachelor’s degree (or equivalent) in Computer Science, Data Science, Information Systems, or a related field. 

  • 5+ years of related practical experience in creating and implementing effective data visualizations, dashboards, and reports, ideally within the insurance industry. 

  • Proficiency in SQL and data visualization tools like Qliksense, PowerBI, D3.js, etc . Some experience in statistical analysis tools and languages like R or Python is desirable. 

  • Understanding of data analysis methodologies, techniques and an ability to work with complex, large data sets. 

  • Hands-on experience with database systems - Cloud technologies (e.g. Azure, AWS), and other database systems - traditional RDBMS (e.g. MS Synapse, SQL Server, Snowflake), and NoSQL databases (e.g. Cosmos, MongoDB, DynamoDB). 

  • Practical knowledge across data extraction and transformation tools and platforms (e.g. Informatica, DataBricks). 

  • Proven success in a collaborative, team-oriented environment, preferably in Scaled Agile model. 

  • Strong Communication Skills, with ability to communicate complex information and data effectively to both technical and non-technical audiences. Familiar with storytelling techniques, using data.