Principal Finance Forward Deployed Engineer (FDE)

Medtronic•Fridley, MN

3d•$123,200 - $184,800•Onsite

About The Position

We are seeking a highly motivated Finance Forward Deployed Engineer (FDE) to join our Finance Analytics and Transformation team. This role sits at the intersection of Finance, Data, Analytics, Automation, and Artificial Intelligence. Unlike a traditional data engineering or analytics role, the Forward Deployed Engineer will work alongside Finance teams to deeply understand business processes, identify high-value opportunities, and rapidly design, deploy, and scale solutions that improve how Finance operates and makes decisions. The ideal candidate combines strong Finance and business acumen with hands-on technical capabilities. This individual will be comfortable participating in forecasting, planning, performance reviews, management reporting, and other Finance processes while also working directly with data, building analytical solutions, automating workflows, and applying emerging AI capabilities. The role requires a strong builder mindset: someone who can move from an ambiguous business problem to a working solution, partner with users to iterate quickly, and ultimately transition successful solutions into scalable enterprise capabilities. At Medtronic, we bring bold ideas forward with speed and decisiveness to put patients first in everything we do. In-person exchanges are invaluable to our work. We’re working a minimum of 4 days a week onsite as part of our commitment to fostering a culture of professional growth and cross-functional collaboration as we work together to engineer the extraordinary.

Requirements

Bachelor's degree
7+ years of experience across Finance, analytics, data engineering, business intelligence, automation, or related functions.
Strong hands-on proficiency with SQL and experience working with complex enterprise datasets.
Experience with visualization and BI platforms such as Power BI, Tableau, or equivalent.

Nice To Haves

Bachelor's degree in Finance, Accounting, Economics, Engineering, Computer Science, Data Science, Information Systems, or a related discipline.
Experience working directly within or supporting FP&A, Commercial Finance, Corporate Finance, or Business Finance.
Strong understanding of core Finance concepts including financial statements, forecasting, planning, variance analysis, management reporting, and business performance.
Demonstrated ability to translate business problems into technical solutions.
Strong analytical problem-solving skills and ability to operate effectively with ambiguous requirements.
Excellent communication skills with the ability to work with both technical teams and Finance/business leaders.
Experience with enterprise Finance platforms such as SAP, Oracle, Anaplan, Workday, Hyperion, OneStream or similar systems.
Experience building applications or workflows using Generative AI and Large Language Models.
Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, APIs, and modern AI development frameworks.
Experience with workflow automation or low-code platforms such as Power Apps, Power Automate, Alteryx, or similar tools.
Understanding of machine learning, statistical modeling, forecasting, and optimization techniques.
Experience deploying analytics or AI solutions into production environments.
Experience working in a complex global enterprise environment.
Experience with Python for analytics, automation, data manipulation, or application development.
Experience with modern data platforms such as Snowflake, Microsoft Fabric, BigQuery, or similar technologies.

Responsibilities

Partner directly with FP&A, Sales Finance, Business Finance, and other Finance teams to understand business processes, pain points, decision workflows, and analytical needs.
Support core Finance team in key Finance processes such as forecasting, annual operating planning, month-end and quarter-end reviews, performance management, variance analysis, management reporting, and executive decision support.
Translate complex or ambiguous Finance problems into clear data, analytics, automation, and AI use cases.
Serve as a bridge between Finance professionals, Analytics teams, Data Engineering, IT, and enterprise technology teams.
Design and build rapid prototypes and minimum viable solutions to address high-value Finance problems.
Develop analytical applications, automated workflows, data products, and AI-enabled solutions using technologies such as Python, SQL, Snowflake, Power BI, APIs, and workflow automation platforms.
Connect and integrate data from ERP, planning, sales, operational, and enterprise data platforms.
Develop reusable data pipelines, analytical components, APIs, and automation frameworks where appropriate.
Rapidly iterate with Finance users based on feedback and demonstrated business value.
Identify Finance processes that can be transformed through Generative AI, machine learning, intelligent automation, or agent-based workflows.
Build and deploy AI-enabled solutions for use cases such as: Financial analysis and variance explanation, Forecasting and scenario analysis, Management reporting, Executive insight generation, Data reconciliation and validation, Financial commentary generation, Ad-hoc business analysis, Workflow and process automation, Data discovery and natural-language analytics, Decision support.
Develop and evaluate prompts, AI agents, retrieval-based solutions, and other GenAI applications using enterprise-approved AI platforms and APIs.
Establish appropriate testing, monitoring, validation, and human-in-the-loop controls for AI-generated outputs.
Work with large and complex Finance and operational datasets to identify patterns, trends, anomalies, and opportunities.
Develop SQL queries, data models, and analytical datasets that enable scalable Finance analytics.
Build analytical models using Python and other modern analytical tools.
Partner with enterprise data teams to improve data availability, quality, lineage, and usability.
Develop dashboards and decision-support tools that translate complex information into actionable business insights.
Identify patterns across Finance use cases and convert successful prototypes into reusable solutions, components, or enterprise capabilities.
Partner with Data, Analytics, IT, and Engineering teams to transition prototypes into secure, scalable, production-ready solutions.
Document solution architecture, business logic, data requirements, and operating processes.
Help establish standards and best practices for developing and deploying AI and analytical solutions across Finance.
Measure adoption, business impact, productivity improvement, and financial value delivered by solutions.