Forward Deployed Engineer (FDE) Data42 (Palantir Foundry)
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 2, 2026. Novartis scores B on the Alion truth index.
Salary Range:
CHF129,500.00 - CHF240,500.00Job Description Summary
Location: Basel, Switzerland#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:
- Bachelors degree in Biology, Bioengineering, Bioinformatics, Biostatistics or related discipline.
- 8+ years of experience working in biomedical research, bioengineering, bioinformatics or related domain.
- Hands-on experience with Palantir Foundry is essential, building and operationalizing solutions (pipelines, ontology, applications, and access controls), with a Foundry-first engineering and delivery mindset.
- Solid experience in partnering with stakeholders to understand challenges and define effective solutions, developing and delivering Proof of Concepts to validate ideas and demonstrate business value.
- 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.
Commitment to Diversity & Inclusion:
We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
Benefits & Rewards
At Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen.
Expected Annual Base Salary Range for role: CHF 129,500 to CHF 240,500 .
The base salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.
In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters.
The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and minimum 14 weeks paid parental leave.
Why Novartis?
Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to learn more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network
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 (Inactive), Organization Awareness (Inactive), Pandas (Python) (Inactive), Python (Programming Language), R Programming, Stakeholder Engagement, Statistical Analysis, Structured Query Language (SQL), Time Series Analysis