Senior Data Engineer

Job description

Delivering AI-ready datasets at scale: Prepare datasets with semantic chunking, embeddings, and freshness guarantees, enabling reliable LLM and RAG workflows across the organization. Supporting global AI teams: Deliver data pipelines on time and ensure data usability for AI, analytics, and platform teams across multiple regions and time zones. Apply now and help change how the world transforms complex data landscapes into actionable insights and turns complex data challenges into new opportunities! Required Iceberg Mastery: Deep experience with Apache Iceberg v2, manifest management, hidden partitioning, and schema evolution. Cloud Data Platforms: Advanced proficiency in Snowflake (External Volumes, Open Catalog), Amazon S3, and AWS EC2. Programming: Mastery of Python (FastMCP, PySpark) and SQL optimization. Enterprise Data Integration: Migrating data from Salesforce and other enterprise applications using APIs, bulk exports, and CDC streams. Infrastructure: Proficiency with Docker, Kubernetes, and Helm for deploying scalable, containerized MCP servers. Data Modeling: Expertise in semantic modeling for LLMs, including Knowledge Graph construction (Neo4j) and vector indexing. Data Modeling & Governance: Schema evolution, metadata management, and maintaining data consistency and quality. Security & Compliance: Knowledge of row-level and column-level security, PII/CRM data protection, and enterprise data governance best practices. Language: Expert-level English (Native or Professional) for global collaboration across time zones.