About the role
As a Senior Business Intelligence Engineer, you will work as a member of the Data Engineering team to ensure the highest quality data is made available for swift analysis and BI report generation. You will help to architect and further develop the data processing pipeline. Part of your responsibilities will be to ensure that our BI platform stays available for key stakeholders. While working closely with analysts and managers, you will get involved in modeling data and create BI reports for managers and executives.
Desired skills & experience
Advanced SQL knowledge (5+ years experience), including optimizing data structure and fast data retrieval from data warehouses such as AWS Redshift.
Strong work experience in data warehousing and business intelligence in an enterprise setting
Deep knowledge of Microsoft BI (Power BI, SSAS/SSRS, DAX)
Ability to build data models dealing with heterogeneous data sources
Ability to work with large-scale data sets
Experience and willingness to work in a fast-moving, agile environment
Nice-to-haves
Experience with Java / Python
Experience with cloud platforms (AWS/Azure)
Knowledge of Tableau solutions
Experience building interactive dashboards providing self-service capabilities
Experience in enabling an organization to become highly data-driven
Experience in data processing with, for example, Spark
Experience working for B2B companies with IT focus
Skills in Machine Learning and advanced analytics
Responsibilities
Support the company-wide implementation of a BI solution (Microsoft Power BI) for governed and self-service analytics
Coordinate with key stakeholders (including BI expert, Analytics team, and Product management) to deliver and optimize data sources to address specified business requirements
Monitor the performance of, and troubleshoot, the BI solution involving test cases and performance tests
Participate in implementation of interactive dashboards / reports on top of data models for various stakeholder groups
Engage in processes ensuring the highest security standards in controlling data access
Manage analytics projects along the development life cycle
Participate in implementation of the data processing pipeline