The Data & Systems Architecture team within Global Procurement Services (GPS) needs to design scalable data architecture, build trusted data ecosystems, and implement advanced analytics solutions to enhance decision-making, improve procurement efficiency, and ensure data accuracy.
Requirements
- Hands-on expertise with MPP databases (e.g., Snowflake, Redshift, BigQuery), cloud platforms (AWS, Azure, GCP), and scalable data pipelines
- Advanced proficiency in Python and SQL with experience developing analytical models (e.g., regression, time-series, neural networks)
- Strong command of tools such as Power BI, AI Analytics tools with proven ability to build data products for broad business consumption
- Deep understanding of data governance practices, including security, privacy, and lifecycle management
- Experience integrating AI/ML solutions into production workflows, including foundation models or LLM-based tools
- Familiarity with unstructured data systems (e.g., MongoDB, Elasticsearch) and vector databases
- Knowledge of enterprise systems and financial planning tools.
Responsibilities
- Lead the design and implementation of robust, secure, and scalable data infrastructure for procurement analytics
- Build end-to-end pipelines and data products to support reporting, forecasting, and AI-powered insights
- Guide high-level strategy and hands-on execution for data quality, governance, and compliance
- Collaborate with business and engineering partners to align data architecture with enterprise needs
- Support the integration of machine learning models and AI tools for use cases like supplier risk, spend forecasting, and process automation
- Promote adoption of cloud-native data tools, reusable frameworks, and enterprise-wide best practices
- Communicate technical concepts clearly to executive stakeholders and drive alignment across technical and business teams
Other
- Members of the Finance organization at select locations will generally be expected to follow a hybrid work model, which includes two days of in-office attendance each week, with limited exceptions.
- At least 6 + years of experience managing or leading technical teams, with the ability to mentor talent and drive results through collaboration
- Mentor and grow a high-performing team of data scientists and analysts, fostering development and alignment with business priorities
- Champion a culture of innovation, experimentation, and ownership within the team
- Passion for driving innovation, operational efficiency, and continuous improvement using data
