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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing scalable data solutions and building robust data pipelines, with proficiency in Palantir Foundry, Python, and AWS services. Capable of delivering complex data engineering solutions in agile environments while integrating AI/ML tools and frameworks.
Highest-signal resume keywords
Palantir FoundryData EngineeringPython ProgrammingAWS ServicesAgile Environments
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline BuildingData IngestionTransformationsTypeScriptPySparkMicroservices ArchitectureDistributed SystemsBig Data TechnologiesPerformance OptimizationDevOps Practices
Soft Skills
Problem-Solving
Tools & Technologies
Palantir FoundryFoundry WorkshopSlateAWS S3AWS GlueAWS AthenaAWS LambdaAWS RedshiftDockerKubernetes
Industry Keywords
Insurance DomainAI/ML ToolsTensorFlowPyTorch
Tech Stack
Tools & technologiesAmazon RedshiftAWSDistributed SystemsDockerJavaScriptKubernetesMicroservicesPySparkPythonPyTorchTensorflowTypeScript
About the role
Key responsibilities & impact- Design scalable data solutions
- Build robust data pipelines
- Model enterprise datasets
- Enable analytics and AI/ML use cases on Palantir Foundry
- Perform data ingestion, pipeline building and transformations
- Build interactive applications using Foundry Workshop, Slate and custom TypeScript frontends
- Deliver complex data engineering solutions in agile environments
Requirements
What you’ll need- 5-10 years of overall experience in data engineering, building and maintaining large-scale data pipelines and platforms
- 2+ years of hands-on experience with Palantir Foundry, including data ingestion, pipeline builder, transformations and working with Foundry datasets and applications
- Experience building interactive applications using Foundry Workshop, Slate and custom frontends using TypeScript
- Proficiency in Python, PySpark, and TypeScript/JavaScript
- Strong experience with AWS services for data processing and storage, including S3, Glue, Athena, Lambda, and Redshift
- Deep understanding of microservices architecture and distributed systems
- Familiarity with AI/ML tools and frameworks such as TensorFlow and PyTorch and their integration into data pipelines
- Experience with big data technologies such as Snowflake
- Strong problem-solving and performance optimization skills
- Exposure to modern DevOps practices, including CI/CD pipelines and Docker and Kubernetes
- Experience working in agile environments delivering complex data engineering solutions
- Prior experience in the insurance domain is highly desirable
- 5+ years of work experience with Data Engineering
- 2+ years of work experience with Palantir
- 3+ years of work experience with Python (Programming Language)