About the role we are seeking adata engineerto supportprofessional services and managed services engagements, with a primary focus onpalantir 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.