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Novartis

Forward Deployed Engineer (FDE) Data42

Posted Yesterday
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In-Office
Cambridge, MA, USA
160K-298K Annually
Senior level
In-Office
Cambridge, MA, USA
160K-298K Annually
Senior level
Embed with domain teams to prototype, build, and productionize data and AI applications on Palantir Foundry. Design data pipelines, ontologies, and user-facing workflows; ensure data quality, access controls, monitoring, and reuse. Lead discovery to delivery, collaborate with product and platform teams, and mentor peers to drive adoption and durable operational solutions.
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Job Description Summary

Location: Cambridge USA;
#LI-Hybrid 3 days/week in office
Internal job title: Forward Deployed Engineer (FDE) Data42
About the Role:
The Forward Deployed Engineer (FDE) at Data42 is an embedded technical delivery leader who partners directly with domain teams to turn high-value problems into working data and AI applications. You will rapidly prototype, iterate, and productionize solutions on Palantir Foundry, bridging users, product, and platform engineering to deliver measurable outcomes. This role blends software engineering, data engineering, and product-oriented problem solving, with a strong emphasis on user workflow adoption and operational durability.


 

Job Description

Key Responsibilities:  

  • Embedded delivery and problem solving: Embed with domain teams to understand workflows, define success criteria, and translate needs into shipped capabilities; Lead discovery, solution framing, and iterative delivery from prototype to production.

  • Build on Palantir Foundry: Design and implement end-to-end solutions in Foundry, including data pipelines, transformations, ontology alignment, and application workflows; Configure and optimize Foundry-based applications to support operational decision-making and repeatable analytics;  Apply Foundry-native patterns for permissions, auditability, performance, and release management.

  • Data engineering and modeling: Ingest, transform, and model diverse datasets to make them usable and trustworthy for analytics and applications; Define data quality checks and ensure datasets are fit for intended use (document assumptions and limitations).

  • Application development and integration: Build user-facing applications or workflow experiences and integrate with upstream and downstream systems as needed; Support deployment, monitoring, and ongoing improvement of production applications.

  • Cross-functional leadership: Partner closely with product managers, data scientists, data engineers, governance, and platform teams to align scope, timelines, and standards; Communicate trade-offs clearly and unblock delivery through technical and stakeholder influence.

  • Enablement and reuse: Create reusable templates, components, and patterns to accelerate future deliveries across Data42; Mentor teammates and contribute to internal documentation, playbooks, and delivery standards.

Essential Requirements:

  • Hands-on experience with Palantir Foundry building and operationalizing solutions (pipelines, ontology, applications, and access controls), with a Foundry-first engineering and delivery mindset.

  • Demonstrated experience delivering software, data, or analytics products in a fast-paced, user-facing environment, with expertise in rapid prototyping to production execution.

  • Strong programming skills and comfort working across data and application layers.

  • Strong user empathy and workflow orientation, with proven ability to work directly with end users, clarify ambiguous requirements, and deliver iteratively.

  • Excellent communication skills and stakeholder management skills, with strong reliability and operational discipline.

Desirable requirements:

  • Experience delivering solutions in regulated or sensitive-data environments, with strong attention to access control and audit needs.

  • Familiarity with product discovery methods (problem framing, value definition, iterative MVP delivery).

  • Experience with analytics, AI, or machine learning enablement within production applications.

The salary for this position is expected to range between $160,300 and $297,700 per year.

The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.

To learn more about the culture, rewards and benefits we offer our people click here.


 

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. 


 

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [email protected] or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.


 

Salary Range

$160,300.00 - $297,700.00


 

Skills Desired

Artificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai, Organization Awareness, Pandas (Python), Python (Programming Language), R (Programming Language), Sql (Structured Query Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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