This role works within the Global Data & AI organization, supporting Daimler Truck’s Quality, Product Engineering, and Electrification domains. The candidate will work hands-on with Palantir Foundry, integrating data from vehicle telematics, battery systems, ECU software release systems, manufacturing plants, and testing environments.
The engineer will build pipelines, develop cleaned data objects, create operational analytics, and support domain teams with real-time insights. They will partner with Data Scientists, Quality Managers, and Software Release teams to ensure data is discoverable, reliable, and usable for AI, validation, and compliance initiatives.
This is a hybrid role blending data engineering, analytics, and low-code/no-code transformations inside Foundry.
Palantir Foundry Engineering
- Build and maintain data pipelines using Foundry tools:
- Code Workbooks, Transformations, Contour, Slate, Quiver
- Perform data ingestion from multiple internal systems (e.g., ALM, PLM, testing systems, ECU logs, telematics platforms).
- Implement validations, cleansing rules, and lineage tracing using Foundry-native features.
- Create Foundry datasets, objects, ontologies, and standardized data models.
Data Analysis & Quality Insights
- Develop dashboards and analytical workflows for:
- Battery performance & anomalies
- ADR quality insights
- Release readiness data
- Manufacturing & end-of-line testing metrics
- Build KPI frameworks for engineering and quality stakeholders.
Cross-Functional Collaboration
- Work with domain SMEs to understand data needs and convert them into Foundry solutions.
- Support Data Scientists with feature-ready datasets and high-quality data pipelines.
- Coordinate with cloud teams, cybersecurity, and governance owners on data policies.
Operational Excellence
- Ensure data reliability, accuracy, and availability for downstream consumption.
- Troubleshoot pipeline issues, data model changes, and schema updates.
- Maintain documentation for datasets, transformations, contracts, and workflows.
Technical Skills
- Bachelor’s/Master’s degree in Computer Science, Data Engineering, Mechanical/Electrical Engineering, or equivalent.
- 1–3 years of experience in:
- Data engineering or analytics
- Data pipeline development
- Python, SQL, PySpark
- Hands-on experience with Palantir Foundry (MANDATORY):
- Code Workbooks
- Foundry Transformations (PySpark/SQL)
- Contour (for data modeling)
- Ontology-based modeling
- Building dashboards in Foundry
- Knowledge of visualization tools (Foundry Slate, Power BI, Plotly).
Automotive Domain Skills (Preferred)
- Basic understanding of:
- ECU software release workflows
- ADR (Automotive Design Review) processes
- Battery/EV telematics data
- Manufacturing/End-of-line test data
- Diagnostic logs (CAN, UDS basics)
- Exposure to vehicle test data or embedded system datasets.
Tools & Platforms
- Python, SQL, Pandas, PySpark
- Palantir Foundry (core requirement)
- Azure (Data Factory, Data Lake), Git
Soft Skills
- Strong analytical mindset with attention to detail.
- Ability to translate business questions into data workflows.
- Good communication and collaboration with global teams.
- Willingness to learn automotive data and systems.
