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# Palantir Data Engineer

- **Company:** ApTask
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Salary:** $156,000.0 - $182,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Business Software, Cloud Computing, Information Engineering, Data Integration, Data Systems, Distributed Computing Environment, Python (Programming Language), Standard Sql, SAP (Applications), Systems Integration, Workflow Management Systems, Enterprise Software Applications, Apache Spark, Data Lakes, Data Management, Machine Learning Operations, Virtual Agents, Data Pipelines
- **Published:** July 1, 2026
- **Apply:** https://www2.jobdiva.com/portal/?a=4ujdnwqsdebu7m13em5f0pt5dw80o500d7dv9cbq5ebzngb7yk0n43mjtefnbx0d&compid=0/jobs/28793064#/jobs/28793064

## About the Role

* 8+ years of experience in Data Engineering, Analytics Engineering, Solution Engineering, AI Engineering, or Enterprise Application Delivery.
 * Hands-on experience with Palantir Foundry and/or Palantir AIP (mandatory).
 * Experience designing and deploying enterprise-scale solutions using data platforms and operational workflows.

Strong knowledge of:

 * Python
 * SQL
 * Spark / Distributed Processing
 * APIs and integration patterns
 * Cloud platforms (Azure / AWS / GCP)

Experience integrating systems such as:

 * SAP
 * MES / Manufacturing systems
 * Data Lakes / Warehouses
 * Enterprise applications

 * Strong understanding of data modelling, ontology concepts, workflow orchestration, and analytics architectures.
 * Ability to engage directly with senior business stakeholders and independently drive problem solving.

Preferred Experience:

 * Experience in Manufacturing / Medical Devices / Life Sciences / Healthcare environments.
 * Exposure to Digital Manufacturing, Supply Chain, Quality, or Regulatory processes.
 * Experience delivering AI / GenAI / Agentic AI solutions in enterprise environments.
 * Exposure to MLOps, AI governance, and observability frameworks.
 * Prior consulting or customer-facing delivery experience.

Success Criteria:

 * Ability to rapidly understand business processes and convert them into deployable solutions.
 * Strong ownership mindset with ability to operate in ambiguity.
 * Demonstrated experience delivering measurable business outcomes through data and AI initiatives.

## Description

* We are looking for an experienced Palantir Forward Deployed Engineer (FDE) to work closely with business stakeholders, product teams, and engineering teams to design and deploy enterprise AI and data solutions.
 * The ideal candidate will bridge the gap between business requirements and technical implementation and drive rapid delivery of production-grade solutions on the Palantir Foundry / AIP ecosystem.
 * This role requires a strong blend of consulting mindset, data engineering, solution architecture, and stakeholder engagement, preferably within manufacturing, medical devices, life sciences, or regulated industries., * Work directly with business and technology stakeholders to understand operational challenges and translate them into scalable digital solutions.
 * Design and implement solutions using Palantir Foundry / AIP across data integration, workflow automation, and AI enablement.
 * Build and operationalize data pipelines, ontologies, business applications, and decision-support workflows.
 * Integrate enterprise systems such as SAP, MES, ERP, CRM, Data Lakes, APIs, and cloud platforms into a unified operating model.
 * Develop production-grade applications and workflows to support manufacturing, supply chain, quality, and operational use cases.
 * Drive workshops, requirement gathering, architecture discussions, and solution demonstrations.
 * Collaborate with engineering teams to ensure scalability, governance, observability, and platform adoption.
 * Support deployment, user adoption, and continuous optimization of solutions.
 * Provide technical leadership and mentor junior team members where required.


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