Foot Locker is a leading brand rooted in sport and powered by style, seeking an innovative Senior Power BI Engineer. The role involves building enterprise-level platform components, driving innovation through collaboration with data science teams, and contributing to the development of a new data lake platform.
Responsibilities:
- Build new data sets, and products helping support Foot Locker business initiatives
- Help grow our data catalog through ingestions of a variety of third party data sources, both internal and external
- Must be able to contribute to self-organizing teams with minimal supervision working within the Agile/ Scrum project methodology
- Participate in the continuous evolution of our schema / data model as we find more data sources to pull into the platform
- Support our Data Scientists by helping enhance their modeling jobs to be more scalable when modeling across the entire data set
- Participate in a collaborative, peer review based environment fostering new ideas via cross-team guilds / specialty groups
- Maintain comprehensive documentation around our processes / decision making
Requirements:
- Bachelors Degree in Computer science or related field
- Minimum 5 years of experience in Analytics Engineering, Business Intelligence Engineering, or Power BI–focused Data Engineering roles
- Extensive experience in data/ semantic modeling (Data Marts, Star/Snowflake, Normalization, SCD2)
- Experience with RDMS(SQL,PostgreSQL),Data warehousing and Business Intelligence
- Deep experience building enterprise Power BI solutions, including semantic models, DAX, performance optimization, and governed self-service analytics
- Advanced SQL programming skills
- Demonstrated experience with agile scrum methodology
- Strong desire to learn new technologies and keep up with the latest technologies in the big data space
- Must possess well-developed verbal and written communication skills
- Public cloud experience, preferably Azure or AWS
- Experience working with large-scale datasets using platforms like Snowflake; familiarity with Spark/Databricks for data preparation is a plus
- Experience with enabling Data Science and Self Service product development with clean, reliable data sets