About the rolewe are seeking a data engineer to support professional services and managed services engagements, with a primary focus on palantir foundry. In this role, you will design, build, and operate robust data pipelines and data models that power analytics, ai/ml, and operational applications for enterprise clients.you will work closely with solution architects, data scientists, forward-deployed engineers, and client stakeholders to translate real-world business problems into scalable, production-grade data solutions. This is a hands-on, delivery-oriented role requiring strong engineering fundamentals, comfort in client environments, and an ability to own data products end to end.key responsibilitiesdata engineering & platform delivery- design, build, and maintain scalable data pipelines for batch and streaming workloads using palantir foundry. - develop and manage foundry pipelines, transforms, and data assets, ensuring data quality, reliability, and performance. - model complex business domains using ontology-driven approaches to enable analytics, applications, and ai use cases. - integrate data from diverse enterprise systems (erp, supply chain, operational systems, apis, files, iot, etc.). - optimize data processing using python, sql, and spark-based tooling within foundry.professional services engagements- collaborate directly with client teams to understand business processes, data sources, and analytical requirements. - translate ambiguous problem statements into well-structured data engineering solutions. - contribute to solution design, technical workshops, and client demos. - support rapid pilots and proof-of-value engagements, balancing speed with production readiness.managed services & operations- support production data platforms in managed service contexts, including monitoring, incident response, and continuous improvement. - implement data quality checks, observability, and operational best practices. - participate in release management, documentation, and handover processes to ensure long-term platform stability.collaboration & best practices- work closely with data scientists, ml engineers, and application developers to enable downstream analytics and ai. - follow and contribute to engineering standards, reusable patterns, and accelerators. - mentor junior team members and contribute to knowledge sharing within the practice.required qualifications- 3+ years of experience in data engineering or related roles. - strong proficiency in python and sql for data processing and analytics. - experience building and operating data pipelines in modern data platforms. - hands-on experience with palantir foundry (or strong equivalent experience with modern data platforms and willingness to specialize). - solid understanding of data modeling, data quality, and pipeline orchestration. - experience working in client-facing or consulting environments. - ability to communicate technical concepts clearly to both technical and non-technical stakeholders.preferred / nice-to-have qualifications- palantir foundry certifications or formal palantir training. - experience with spark / pyspark, streaming data, or large-scale distributed systems. - experience supporting production platforms in managed services or sre-style environments. - familiarity with analytics, ml workflows, or ontology-based data modeling. - background in industries such as manufacturing, supply chain, energy, life sciences, or logistics.