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Job Description
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.
Qualifications
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.
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