The Role
We are seeking a highly skilled and enthusiastic Senior Business Intelligence Engineer to join our Enterprise Data Analytics and Insights team. The ideal candidate will play a crucial role in transforming data into actionable insights for the business. You will lead, design and develop complex data assets such as impactful visualization reports, dashboards and self-service data products to aid decision making. You will collaborate with stakeholders to understand business needs, have a consultative approach and develop quantitative and qualitative solutions, apply predictive/prescriptive modeling to address issues and possess compelling storytelling skills to effectively articulate business insights. You are expected to have strong statistical and business analytics skills, build analytic solutions and support the dynamic needs of the business teams. This role requires flexibility and the ability to thrive in a fast-paced environment with quick turnaround times.
What You'll Do:
- Define and implement best practices and patterns for creating scalable, high-quality visualizations using Power BI, Dash, and React.
- Conduct in-depth statistical and quantitative analysis on complex data to develop insights and address business issues.
- Collaborate with stakeholders to identify opportunities and provide rapid analytic solutions as a consultant.
- Gain a deep understanding of the business and its domain, think strategically and comprehensively, and effectively communicate complex solutions through storytelling.
- Retrieve data from different source systems, perform ETL operations, handle large volumes of data, and have expertise in Data Bricks, SQL, Power BI or equivalent.
- Collaborate with data analysts, data engineers, data scientists and business stakeholders to understand data requirements and visualization needs.
- Work with cross-functional teams to identify key metrics and KPIs for tracking business performance and progress.
- Collaborate with UX/UI designers to ensure a seamless and user-friendly experience in data visualizations.
