We are hiring a Senior Palantir Data Engineer with deep expertise in building large-scale, cloud-native data pipelines, orchestration frameworks, and operational data services.

This role demands strong experience with Palantir Foundry, AWS, Python, and PySpark, along with a proven track record in architecting data solutions in complex enterprise environments.

As a senior engineer, you will lead design decisions, mentor junior team members, and drive the implementation of secure, scalable, and high-performance data infrastructure.

Key Responsibilities :

- Architect and develop advanced data pipelines, ingestion frameworks, and orchestration flows using PySpark, Palantir Foundry, and AWS services.

- Lead the development of domain-specific Foundry ontologies, code workbooks, and operational pipelines.

- Design reusable, scalable components and workflows for data cleansing, enrichment, and transformation.

- Drive infrastructure-as-code adoption and CI/CD pipeline integration using GitLab and AWS developer tools.

- Champion observability and operational excellence by implementing robust monitoring and alerting systems.

- Collaborate closely with stakeholders across business, analytics, and engineering to align platform capabilities with strategic goals.

- Provide technical leadership in architectural reviews, design sessions, and mentoring of junior engineers.

- Contribute to platform governance and policy enforcement, including data security and compliance (e.g., IAM best practices).

Technical Skills Required :

- Programming : Expert-level skills in Python and PySpark

- Cloud Platform : Advanced hands-on experience with AWS (S3, Glue, EMR, Lambda, IAM, CloudWatch, ECS)

- Platform Expertise : In-depth experience with Palantir Foundry, including Ontology, Object Builders, Code Workbooks, and pipeline orchestration

- DevOps & CI/CD : Git, GitLab, Bitbucket, Jenkins, AWS CodePipeline/CodeBuild

- Data Modeling & SQL : Strong SQL optimization and schema design skills

- Linux : Proficiency in system-level scripting and data management in Unix environments

- Monitoring & Logging : Tools such as Prometheus, Datadog, ELK stack, or AWS-native tools

Qualifications :

- Bachelors or Masters degree in Computer Science, Data Engineering, or related field

- 10+ years of experience in designing, building, and operating large-scale data systems

- Proven experience leading high-impact engineering teams or large-scale data transformation programs

- Ability to assess business data needs and translate them into scalable technical architectures

- Strong stakeholder management and communication skills across engineering and product teams