Data Engineer

Palantir Data Engineer – Senior Associate (5–9 Years)

Our Analytics & Insights Managed Services team brings a unique combination of industry expertise, technology, data management and managed-services experience to create sustained outcomes for our clients and improve business performance. We empower companies to transform their approach to analytics and insights while building your skills in exciting new directions. Have a voice at our table to help design, build and operate the next generation of software and services leveraging the power of Palantir.

Job Requirements and Preferences

Basic Qualifications

• Minimum Degree Required:

Bachelor's degree in computer science, Data Engineering, Data Science, Information Systems, or a related technical field

• Minimum Years of Experience:

5–9 years of hands-on data engineering experience, including 2+ years working with Palantir Foundry or Gotham

Preferred Qualifications

• Degree Preferred:

Master's degree in data science, Analytics, Computer Science, Information Systems, or related discipline

• Preferred Fields of Study:

Data Processing/Analytics/Science, Management Information Systems, Software Engineering

Preferred Knowledge & Skills

As a Senior Associate, you architect, develop, and optimize end-to-end data solutions on Palantir platforms, while mentoring junior teammates. You demonstrate deep technical acumen across:

• Palantir Platform & Data Modeling

– Design and maintain Foundry ontologies, datasets, and code workbooks

– Build reusable transforms and data models that underpin business workflows

• Cloud-Scale Data Engineering

– Develop and optimize ETL/ELT pipelines in Python (PySpark) and SQL

– Integrate diverse sources (batch, streaming, JDBC/ODBC, REST/Kafka/Kinesis) into Foundry

• Performance & Scalability

– Tune high-volume, latency-sensitive data feeds for both batch and event-driven patterns

– Employ caching, partitioning, and parallelization best practices

• DevOps & Automation

– Implement CI/CD pipelines with Git, Docker, Kubernetes, and infrastructure-as-code

– Automate testing, deployment, and versioning of Foundry code

• Data Governance & Quality

– Leverage Foundry’s built-in lineage, access controls, and monitoring capabilities

– Collaborate with data stewards to define quality metrics and enforce policies

• Cloud & Infrastructure

– Hands-on experience with AWS, Azure or GCP services (e.g., S3, Glue, Dataflow) supporting Palantir deployments

– Understand network security, IAM, and multi-cloud/hybrid architectures

• Collaboration & Mentorship

– Partner with data scientists, analysts, and architects to translate requirements into robust solutions

– Coach junior engineers, share best practices, and drive continuous improvement

• Communication & Delivery

– Present technical designs and performance analyses to senior stakeholders

– Contribute accelerators, playbooks, and internal tools to accelerate client delivery