Palantir Foundry

Bachelor of Engineering or equivalent undergraduate degree.
5–8 years of overall experience in data engineering and platform delivery responsibilities.
Hands-on experience delivering data engineering solutions using Palantir Foundry.
Proven ability to lead technical delivery, manage priorities, and coordinate with cross-functional stakeholders.
Strong understanding of data pipeline design, data quality controls, and operational support for production workloads. Preferred Qualifications:
Experience leading small-to-mid sized engineering teams and driving best practices across delivery and operations.
Strong experience with data governance concepts including lineage, access controls, and auditability in enterprise environments.
Demonstrated success in building reusable data assets and standardized patterns to accelerate delivery across use cases.
Experience working with large-scale datasets and optimizing performance, reliability, and maintainability of pipelines.
Ability to communicate technical decisions clearly to both technical and non-technical stakeholders. Key Responsibilities:
Lead end-to-end delivery of data engineering solutions on Palantir Foundry, from requirement discovery to production rollout.
Design and implement scalable data pipelines, transformations, and curated datasets aligned to business use cases using Foundry tooling (e.g., Pipeline Builder/Code Repositories, Ontology, and Workshop/Contour where applicable).
Define data modeling approaches and ensure high data quality through validation, reconciliation, and monitoring practices within Foundry.
Establish engineering standards for versioning, testing, documentation, and release management within Foundry workflows, including CI/CD patterns for Foundry repositories.
Collaborate with product owners, analysts, and downstream consumers to deliver reliable, well-governed data products, leveraging Foundry’s Ontology to enable consistent business semantics and consumption.
Configure and maintain Foundry data governance capabilities such as lineage, metadata management, and dataset certification to improve trust and auditability.
Troubleshoot pipeline failures and performance bottlenecks in Foundry; drive root-cause analysis and preventive improvements, including optimization of transforms and compute usage.
Ensure solutions adhere to security, access controls, and governance requirements across datasets and workflows, implementing least-privilege access and policy-based controls in Foundry.
Mentor engineers, conduct technical reviews, and provide guidance on Foundry best practices, reusable patterns, and implementation choices.
Partner with platform and operations teams to define operational readiness (monitoring, alerting, SLAs/SLOs, incident response) for Foundry-based production workloads. Good to have skills: SQL, Python, Data Modeling, ETL/ELT Design Patterns, Data Quality Frameworks, CI/CD for Data Pipelines, Monitoring & Observability, Cloud Data Platforms, Agile/Scrum

Skills
Python, CI/CD, SQL, Data Modeling, ETL, Agile, Scrum, Documentation

Work arrangement
No