Data Modeler

at  Lab49

LAB49 is seeking a senior-level, client-facing Data Modeler with Analytics experience to join our team.
The ideal candidate will have a strong background in data modelling and business intelligence, reporting, analytics tools, with strong hands-on experience with Amazon Redshift, Amazon QuickSight, and/or Power BI.
The successful candidate will work directly with major financial institutions and play a critical role in designing, developing, and maintaining data-driven decision-making infrastructure across clients.

REQUIREMENTS:

• Minimum 7 years of relevant experience
• Proficiency with Amazon Redshift, Amazon QuickSight, and/or Power BI or other reporting tools and data platforms.
• Experience in SQL and database design.
• Knowledge of Python or other programming languages.
• Experience in cloud data infrastructure and services.
• Familiarity with data warehousing concepts and best practices.
• Strong analytical and problem-solving skills.
• Consulting mindset: work independently, become a trusted consultant to the client and identify potential opportunities for engagement expansion.
• Excellent communication and collaboration skills.
• Experience within the financial industry is a plus.
• Experience working in a consulting environment is highly desired.
• Bachelor’s degree in Business, Finance, Data Science, or a related field.

• Data Modelling: design, implement, and maintain data models in Amazon Redshift to support various technical and business needs.
• Reporting & Analytics: create reports, visualizations, dashboards and supporting data assets using Amazon QuickSightand Power BI.
• Collaboration: work closely with data engineers, analysts, and business stakeholders to understand data and visualization requirements and deliver appropriate designs and solutions.
• Documentation: maintain comprehensive documentation of data models and visualizations.
• Best Practices: stay up-to-date with industry best practices and emerging trends in data modelling and analytics technologies and apply them to the business and technical domain.