Design, build, and scale a core data platform that powers data-driven insights across JLL, consolidating siloed systems into a unified data layer
Job Summary
Design, build, and scale a core data platform that powers data-driven insights across JLL, consolidating siloed systems into a unified data layer.
Build features and full-stack applications that bridge structured and unstructured data for downstream consumption, enabling smarter search, contextual recommendations, and automated report generation.
Partner closely with Business, Product, and Engineering teams to translate stakeholder needs into data products with a rapid, iterative turnaround.
Matching Summary
Design, build, and scale a core data platform that powers data-driven insights across JLL, consolidating siloed systems into a unified data layer.
Skills & Requirements
Must-have
Scalable, fault-tolerant architectures
Cloud platforms (Azure or AWS)
Python, Java, or Scala
PySpark/Spark for distributed data processing
Backend development (Java and Spring Boot)
Data modeling and architecture
SQL, NoSQL, and AI-centric databases
Nice-to-have
Modern frontend frameworks
Semantic layers or knowledge graphs
Streaming tools (Kafka, Spark Streaming)
DevOps principles, CI/CD, containerization
LLM-driven workflows
AI-powered development tools
Key Requirements
4-6 years of data engineering experience
2-3 years of cloud platform experience
Strong software engineering experience
Experience with SQL, NoSQL, and AI-centric databases
Bachelor's degree in Computer Science or related field (preferred)