Data Engineer

Data EngineerDuration: 12+ months with possible extension Location: Westmont, ILRequired Qualifications7+ years of experience in data engineering and Big Data development, including multiple large, complex project deliveries.Strong hands-on experience with cloud data platforms on Azure or AWS, including services such as Databricks, Azure Data Factory, Synapse, AWS Glue, or EMR.Advanced proficiency in Python and SQL, with deep expertise in PySpark/Spark for distributed data processing at scale.Proven expertise in data modeling and data architecture, including advanced database design and optimization across SQL (e.g., Azure SQL, PostgreSQL) and NoSQL (e.g., Cosmos DB, MongoDB) stores.Experience designing and building API services and integrating data platforms with downstream applications.Hands-on experience with LLM-driven workflows, RAG architectures, or Model Context Protocol (MCP) integrations — or demonstrable experience preparing enterprise data for AI/agentic consumption.Track record of leading workstreams and driving technical decisions across teams as a senior individual contributor.Availability to work on a contract basis with structured deliverables, and to complete thorough documentation and knowledge transfer.Preferred QualificationsExperience with streaming technologies such as Kafka, Spark Streaming, or Azure Event Hubs.Familiarity with vector databases (e.g., Pinecone, Weaviate) and knowledge/graph databases (e.g., Neo4j).Experience with orchestration frameworks for LLM applications (e.g., LangChain, LlamaIndex) and advanced prompt engineering.Working knowledge of DevOps practices: CI/CD pipelines, infrastructure as code (Terraform), and containerization (Kubernetes).Exposure to commercial real estate, CRM, or transaction/deal-pipeline data domains.Experience with data governance frameworks and compliance standards (GDPR, CCPA).Key attributesProblem-Solving Skills: Breaks down complex, ambiguous data challenges into pragmatic, well-architected solutions.Ownership & Drive: Takes full accountability for deliverables from design through production handoff, without needing close supervision.Technical Influence: Drives sound technical decisions across teams through evidence, prototypes, and clear architectural reasoning.Communication: Explains complex technical concepts and trade-offs clearly to engineers, product partners, and stakeholders.Collaboration: Works effectively with JLL engineers, product owners, and cross-functional teams, prioritizing continuity and knowledge sharing.Adaptability & Speed: Delivers high-quality results quickly within a fixed engagement window, adjusting to evolving priorities.