Data Engineer

📢 We are looking for a Data Engineer who thrives at the intersection of data engineering, AI, and real-world business impact. In this role, you will design and build production-ready data pipelines and feature engineering workflows that power operational AI, ML, and GenAI use cases on modern data platforms. You’ll work closely with clients’ technical teams, architects, and product managers, gaining deep insight into complex data ecosystems and translating them into scalable, secure, and high-quality solutions. This is a hands-on, client-facing role for someone who enjoys ownership, technical depth, and tangible outcomes 💪✅ Requirements:Commercial experience with Palantir 3–5 years of experience in production-grade data engineeringAt least 3 years working with enterprise-class data platformsProven experience designing and deploying large-scale data pipelinesStrong SQL and Python skillsHands-on experience with relational and non-relational databasesUnderstanding of ontologies and data platform design patternsStrong communication skills and the ability to collaborate with both technical and non-technical stakeholders✨ Nice to have:Experience in the insurance sectorBackground in building client-facing applications, demos, or PoCsExperience implementing enterprise security architecturesDomain exposure to finance, healthcare, or manufacturing✅ Responsibilities:Build robust data pipelines and workflows to prepare data for ML and GenAI use casesImplement MLOps/LLMOps tooling for enterprise-scale clientsDesign production-ready, high-quality solutions using modern engineering practices and a pragmatic mindsetExplore diverse data sources and define efficient, maintainable transformationsDesign ontology models and integration pipelines connecting 5+ systemsBuild demo applications and PoCs that accelerate data-driven business decisionsImplement security architectures and permission models aligned with enterprise standards✅ Benefits:Work on cutting-edge AI, ML, and GenAI projects with real business impactExposure to complex enterprise environments and top-tier clientsHigh level of technical ownership and autonomyOpportunity to influence architecture, standards, and best practicesCollaborative, expert-level team culture with strong knowledge sharingContinuous learning support (training, certifications, conferences)Flexible working model and a healthy work-life balanceCompetitive compensation aligned with experience and impact