Medtronic
AI/DataScienceEngineerII(DataEngineer)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI/Data Science Engineer II(Data Engineer) at Medtronic. Skills: Data Engineering, Analytics Engineering, Finance Data, ETL/ELT, Data Modeling. Design data architectures. Optimize data architectures”
Industry & Context.
Data-driven decision making
3-4 days per week of overlapping working hours with the U. S. team
What They're Looking For.
Must Have
Bachelor's degree in engineering, Finance, or related field, 5+ years of experience in Data Engineering, Analytics Engineering, or Finance Data roles, Understanding of financial processes, Hands-on experience with SQL, Hands-on experience with Snowflake, Hands-on experience with ETL/ELT development, Experience working with enterprise financial systems
Nice to Have
MBA in Finance preferred, Experience with cloud platforms, Familiarity with Python for data processing, Familiarity with Spark for data processing, Exposure to Power BI, Experience supporting financial planning, Experience supporting revenue analytics, Experience supporting sales performance reporting, Knowledge of data governance, Knowledge of data lineage, Knowledge of financial controls frameworks, Proven ability to work independently, Proven ability to manage multiple priorities, Communication skills, Proactive mindset, Organizational ability, Time-management ability
What You'll Do.
Design data architectures
Optimize data architectures
Design feature-ready data models
Design real-time pipelines
Design near-real-time pipelines
Design governed datasets
Translate finance processes into data models
Design ETL/ELT pipelines
Build ETL/ELT pipelines
Maintain ETL/ELT pipelines
Support financial reporting
Support financial planning
Support financial analytics
Partner with finance stakeholders
Partner with data engineers
Partner with IT teams
Support downstream analytics
Support Power BI dashboards
Support forecasting models
Support AI/ML initiatives
Identify automation opportunities
Identify standardization opportunities
Optimize data pipelines
Evaluate data architecture
Enhance data architecture
How You'll Work.
Team & Collaboration
Finance teams; Data Science teams; Engineering teams; Finance stakeholders; Data engineers; IT teams
Communication Scope
Translate between finance and technical teams
Full Job Description
At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world. # **A Day in the Life** As a Data Engineer for the Reporting, Analytics & Insights (RAI) COE within Global Finance at Medtronic, you’ll have an opportunity to contribute to the world’s largest medical device company. This dynamic role within a multicultural environment fosters career growth and is critical to driving digital transformation and operational excellence across financial operations. You will work closely with Finance, Data Science, and Engineering teams to develop interactive visualizations that drive data accessibility. This role requires an average of 3-4 days per week of overlapping working hours with the U.S. team to ensure seamless collaboration. **Responsibilities may include the following and other duties may be assigned:** * Enable scalable AI/ML use cases by designing and optimizing data architectures, including feature-ready data models, real-time/near-real-time pipelines, and governed datasets that support advanced analytics, forecasting models, and enterprise AI initiatives. * Finance Domain Data Ownership: Translate finance processes (FP&A, revenue, cost, margin, forecasting) into scalable and governed data models. * Data Engineering & Pipeline Development: Design, build, and maintain robust ETL/ELT pipelines using modern data platforms (e.g., Snowflake, Azure). * Data Modeling for Finance: Develop optimized data models (fact/dimension structures) to support financial reporting, planning, and analytics. * Business & Technical Collaboration: Partner with finance stakeholders, data engineers, and IT teams to align data architecture with business needs. * Enable Advanced Analytics: Support downstream analytics, including Power BI dashboards, forecasting models, and AI/ML initiatives. * Automation & Process
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