Enterprise Data & AI Integration Co-Op, Summer 2026

This posting is submitted in anticipation of future roles at Edwards.

Program participants could be placed at our corporate headquarters in Irvine, California Location. Please visit Edwards.com for information on our locations.

Make a meaningful difference to patients around the world. Our University Programs are designed to help early-career professionals contribute to solutions that transform patient lives. We also believe in investing in the future of our talented people across the globe, including early career professionals seeking to explore and establish themselves within the medical device industry. We’ll provide you with the opportunity to thrive in a dynamic environment where you can make innovative contributions. As an Intern with us, you’ll find motivation and inspiration in a culture that emphasizes passion for patients as you discover your own strengths.

About the Team (EDAIx)

Enterprise Data, Analytics & AI Integration (EDAIx) is building the data foundation that powers enterprise analytics and accelerates responsible AI across Edwards. We operate at the intersection of data platforms, analytics engineering, governance, reliability, and AI enablement—standardizing how data products are built, operated, and consumed across the company.

This Co‑Op is ideal for a student who wants to work on real platform and engineering problems, ship meaningful improvements, and learn how modern enterprises scale data + AI safely and efficiently.

What We Offer

• Meaningful, production‑relevant work with real ownership and mentorship.

• Exposure to enterprise-scale data modernization and AI readiness initiatives.

• Opportunity to build portfolio‑worthy deliverables that will be used by real teams.

Key Responsibilities

Co‑Op projects are matched to your strengths and interests while supporting active EDAIx priorities. You may contribute across multiple areas such as:

1) Data Platform & Modernization (Lakehouse / Backbone)

• Support development of reusable platform patterns for ingesting, transforming, and serving data products.

• Help improve interoperability between storage and compute (e.g., “right engine for the job” patterns).

• Contribute to automation that improves developer experience, onboarding speed, and operational consistency.

2) Standardized Engineering Delivery (CI/CD, Templates, Reliability)

• Assist with defining and implementing data engineering standards (pipeline conventions, testing, documentation, change control).

• Build or enhance reusable templates (job scaffolds, repo structure, pipeline patterns, environment conventions).

• Support CI/CD concepts for data workflows (version control, validation checks, release discipline).

3) BI & Analytics Modernization (Power BI + Semantic Standards)

• Support modernization efforts that reduce BI tool sprawl and improve self‑service analytics.

• Help with governance/operating model artifacts (workspace standards, dataset quality, performance guidance, enablement materials).

• Assist with migration support activities (dependency mapping, report rationalization, validation, and documentation).

4) Data Observability, Quality & Operational Excellence

• Help define and instrument data reliability signals (freshness, volume, schema drift, quality checks).

• Build basic dashboards or monitoring views to improve trust and reduce incidents.

• Contribute to runbooks and “how to respond” playbooks for common pipeline/data issues.

5) AI Enablement & Integration Patterns (AI‑Ready Data)

• Support AI‑ready data efforts: curated datasets, documented interfaces, and repeatable patterns that help AI initiatives scale.

• Help create enablement assets (docs, examples, lightweight prototypes) that simplify adoption for other teams.

6) Communication & Documentation (High-Impact, Not Busywork)

• Create clear, professional documentation: diagrams, standards pages, onboarding guides, and project readouts.

• Present progress succinctly to technical and non‑technical stakeholders.

Required Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related field.

• Ability to work full-time for the duration of the Internship (May/June 2026 - December 2026)

• Current enrollment as a student at an accredited university for