Starbucks is looking to solve real-world issues by enabling AI and making an impact at the enterprise level through better data management and engineering.
Requirements
Strong understanding of relationship data
Deep experience in Graph data technologies
Comfortable with Taxonomy and Ontology
Strong SDLC knowledge. Leads the development of and adherence to development standards. Acts as a consultant to Data Science and Analytics teams to follow engineering practices.
Builds and maintains a coherent set of tools and technologies to support an enterprise Data and Analytics capability.
Develops and documents implementation patterns, supporting common requirements and business needs.
Applies the most appropriate technology to the specific use case.
Responsibilities
Develops and maintains a data strategy that creates foundational data products supporting all Starbucks data personas and use cases.
Develops a framework of data Products that supports all data usage use cases, including Operational reporting, Analytics, and AI/ML.
Strong understanding of Information architecture and the development of an enterprise data landscape supporting, Data Science, Self-service and AI.
Deep understanding on the data life cycle of an enterprise.
Strong understanding of relationship data
Deep experience in Graph data technologies
Comfortable with Taxonomy and Ontology
Other
Leadership experience – 4+ years. Does not have to be limited to technology sector experience, Military or EMS leadership experience a bonus.
Hands on Coding experience – 3+ years.
Project or Product execution – 5+ years.
Enterprise Data experience – 5+ years.
We believe we do our best work when we're together, which is why we're onsite four days a week.
