• Report to the Vice President of Engineering • Collaborate with other engineers and mentor junior staff • Design scalable systems and drive adoption of AI-assisted code • Understand product requirements and see through to execution

• Drive technical strategy and roadmap. • Lead end-to-end delivery of large, cross-functional projects. • Own architecture, reliability, performance and cost for critical systems. • Define SLOs/SLIs and lead incident response. • Improve observability, automation and operational readiness. • Align stakeholders and remove blockers. • Mentor and grow engineering talent. • Represent engineering internally and externally.

• Fazer parte de nossas squads multidisciplinares; • Participar do desenvolvimento de novas features; • Ajudar a manter nosso backlog de manutenção saudável; • Realizar testes de unidade (sempre contando com o apoio de nossos especialistas); • Aprender nossa regra de negócio e aplicá-la nas demandas do dia-a-dia;

Role Description The Senior Data Platform Engineer will support development and operation of a modern data environment supporting Navy financial management and audit artifact traceability initiatives. The role focuses on building and maintaining data pipelines, ingestion workflows, and transformation processes within Palantir Foundry and the Jupyter data platform environment. The engineer will work alongside ontology engineers and platforms lead to ingest, transform, and manage datasets that support artifact traceability, audit response reporting, and operational data applications. Key Responsibilities - Data Pipeline Development: - Develop and maintain Python-based data pipelines and transformation workflows within Palantir Foundry and the Jupyter platform. - Build ingestion pipelines integrating financial management, logistics, property, and other enterprise datasets. - Implement transformation logic to prepare raw datasets for curated data layers and ontology population. - Data Platform Operations: - Support dataset lifecycle management including refresh schedules, validation checks, and pipeline monitoring. - Troubleshoot pipeline failures and assist in maintaining platform data reliability and stability. - Maintain dataset lineage awareness and support platform data integrity practices. - Data Integration and Support: - Assist with integrating enterprise system data into the platform environment. - Collaborate with ontology engineers to ensure pipelines populate ontology objects and platform data structures correctly. - Document pipelines and transformation logic to support maintainability of the platform. Qualifications - Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related technical field (or equivalent experience). - 4–7 years experience in data engineering or platform engineering roles. - Experience developing Python-based data pipelines. - Experience building ETL/ELT pipelines and data transformation workflows. - Experience working with enterprise data platforms such as Palantir Foundry, Databricks, AWS data platforms, or similar distributed data environments. - Experience integrating datasets from enterprise systems (ERP, financial systems, logistics systems, etc.) preferred. Requirements - Strong Python development skills for data processing and pipeline development. - Experience with SQL and data transformation frameworks. - Familiarity with distributed data platforms and large-scale data environments. - Strong troubleshooting and problem-solving skills in data pipeline operations. - Ability to collaborate with platform engineers, ontology engineers, and functional stakeholders. Benefits - Salary Range: $90-$115k per year.