JLL empowers you to shape a brighter way .
Data Engineer 2 (Full Stack)
About JLL and JLL Technologies
JLL is a leading professional services firm that specializes in real estate and investment management.
Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions.
In doing so, we will build a better tomorrow for our clients, our people, and our communities.
JLL Technologies is a specialized group within JLL.
At JLL Technologies, our mission is to bring technological innovation to commercial real estate.
We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally.
Our goal is to leverage technology to increase the value and liquidity of the world's buildings, while enhancing the productivity and happiness of those that occupy them.
What this job involves
What you'll get to do
Key responsibilities
Data Pipeline Development : Build and maintain reliable data pipelines that consolidate regional and country-specific systems into a unified data platform.
Data Integration : Integrate structured and unstructured data sources to enable advanced analytics, model building, and insight generation.
Data Enablement : Contribute to the design of semantic layers and knowledge graphs to make commercial real estate data discoverable and consumable by stakeholders and AI/ML systems.
Technical Implementation : Participate in technical solutioning across the project lifecycle, from discovery and architecture through deployment and iteration.
DevOps and Quality : Deploy and monitor data products on cloud platforms with observability, telemetry, data lineage, and auditability to ensure outputs are traceable and compliant.
Cross-functional Collaboration : Work closely with Business, Product, and Engineering teams to translate stakeholder needs into data products with rapid turnaround.
Who you are
Qualifications and skills
Required Qualifications
2-4 years of experience in data engineering and Big Data development, with exposure to scalable, fault-tolerant architectures.
1-2 years of hands-on experience with cloud platforms such as Azure or AWS (e.g., Databricks, Azure Data Factory, Synapse).
Solid proficiency in a server-side programming language such as Python, Java, or Scala, with experience in PySpark/Spark for distributed data processing.
Backend development experience, including Java and Spring Boot.
Understanding of data modeling principles and how data structures affect retrieval and analytics.
Basic understanding of machine learning concepts and model deployment.
Experience working with SQL (e.g., Azure SQL), NoSQL (e.g., Cosmos DB, MongoDB), and emerging AI-centric databases such as vector or knowledge/graph databases.
Ability to write optimized SQL and work with large datasets.
Preferred Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field.
Experience with modern frontend frameworks such as React, Angular, or Vue.js.
Exposure to semantic layers or knowledge graphs.
Hands-on experience with streaming tools like Kafka or Spark Streaming.
Understanding of DevOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes).
Exposure to LLM-driven workflows, prompt engineering, or orchestration tools (e.g., LangChain, LlamaIndex, CrewAI).
Familiarity with AI-powered development tools (e.g., Codex, Claude, Cursor) as part of an AI-augmented software development lifecycle.
Key attributes
Problem-Solving Skills : Strong analytical and systems-thinking abilities.
Ownership & Drive : A proactive, self-motivated individual with growing ownership for the platform and products you build.
Collaboration : A team-first attitude with ability to collaborate effectively with business stakeholders, product managers, and distributed engineering teams.
Communication : Good verbal and written communication skills, with an ability to explain technical concepts clearly.
Adaptability & Speed : The ability to work at a fast pace and translate business needs into delivered data products with quick turnaround.
Location :
On-site -Jalisco,MEX
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