What you'll get to do
As a Staff Software Engineer, you will provide technical leadership and strategic direction for our data ecosystem. Your "customers" span the entire organization—including executive leadership, brokers, clients, application teams, data scientists, and external partners—and your mission is to architect and deliver an enterprise data platform that generates competitive advantage through market-leading insights. You will partner with executive leadership, Product, Engineering, and Business teams to define the long-term roadmap and technical strategy. This is an opportunity to make transformative impact by establishing the foundational data architecture for intelligent applications, Agentic AI workflows, LLM-powered assistants, and next-generation analytics capabilities.
Key responsibilities
Strategic Architecture and Vision: Define and drive the enterprise data platform strategy, consolidating global systems into a unified, governed, and scalable data architecture that serves as the foundation for JLL's data-driven future.
Technical Leadership: Provide technical leadership across multiple teams and initiatives, setting architectural standards, design patterns, and best practices for data engineering across the organization.
Advanced Data Integration: Architect sophisticated integration strategies for structured and unstructured data sources, enabling advanced analytics, AI/ML model building, and real-time insight generation at enterprise scale.
Platform and Application Innovation: Lead the design and development of advanced full-stack applications and platform capabilities that seamlessly bridge structured and unstructured data, enabling intelligent search, contextual AI-driven recommendations, and automated insight generation.
Enterprise Integration Architecture: Design and implement enterprise-grade integration frameworks, including comprehensive API strategies, integration patterns, and Model Context Protocol (MCP) implementation, enabling seamless data consumption across applications, Agentic AI systems, and analytics platforms.
ML/AI Platform Strategy: Architect production-grade machine learning and AI platforms, establishing robust MLOps practices for model training, deployment, monitoring, and governance at scale.
AI and Knowledge Architecture: Design sophisticated semantic layers, ontologies, and knowledge graphs that make commercial real estate data intelligently discoverable and consumable by both human stakeholders and advanced AI/ML systems.
Technical Excellence and Innovation: Lead architectural reviews, technology evaluations, and proof-of-concept initiatives. Drive adoption of emerging technologies and best practices across the data engineering organization.
Enterprise DevOps and Governance: Establish enterprise-grade DevOps practices, observability frameworks, data governance standards, lineage tracking, and compliance mechanisms ensuring data products are production-ready, auditable, and meet regulatory requirements.
Cross-functional Leadership: Partner with C-level executives, Product leadership, and Engineering leadership to align data platform capabilities with business strategy. Translate complex business challenges into technical roadmaps with measurable outcomes.
Team Development and Mentorship: Mentor and develop data engineers across all levels, conducting technical reviews, providing architectural guidance, and fostering a culture of technical excellence and innovation.
Stakeholder Management: Serve as the technical voice for data engineering in executive forums, effectively communicating complex technical concepts, trade-offs, and strategic recommendations to diverse audiences.
Who you are
You are a distinguished technical leader with deep expertise in building enterprise-scale data platforms and the applications that leverage them. You think strategically about data architecture, balancing immediate business needs with long-term scalability and maintainability. You are energized by complex technical challenges and excel at designing elegant solutions to seemingly intractable problems. You have a proven track record of leading high-performing teams and influencing technical direction across organizations. You thrive in dynamic environments where you can drive innovation while maintaining operational excellence. You demonstrate exceptional ownership and are recognized as a thought leader who elevates the capabilities of everyone around you.
Qualifications and skills
Required Qualifications
10+ years of experience in data engineering and Big Data development, with extensive experience architecting and delivering enterprise-scale, fault-tolerant data platforms.
5+ years of hands-on experience with cloud platforms such as Azure or AWS, including advanced services (e.g., Databricks, Azure Data Factory, Synapse, AWS Glue, EMR, Redshift).
Expert-level proficiency in multiple server-side programming languages including Python, Java, and Scala, with deep expertise in PySpark/Spark for distributed data processing at scale.
Extensive software engineering experience in backend development, including advanced Java, Spring Boot, and microservices architectures.
Proven expertise in data modeling, data architecture, and designing data systems that balance performance, scalability, maintainability, and cost.
Deep understanding of machine learning lifecycle, MLOps practices, model governance, and production ML systems.
Extensive experience working with diverse data technologies including SQL databases (e.g., Azure SQL, PostgreSQL), NoSQL databases (e.g., Cosmos DB, MongoDB, Cassandra), and AI-centric databases such as vector databases (e.g., Pinecone, Weaviate) and knowledge/graph databases (e.g., Neo4j, Amazon Neptune).
Demonstrated ability to architect and optimize complex data systems for performance, reliability, and cost-efficiency.
Proven track record of technical leadership, including mentoring senior engineers and leading cross-functional initiatives.
Preferred Qualifications
Master's degree , Engineering, Data Science, or a related field.
Extensive experience with modern frontend frameworks such as React, Angular, or Vue.js, with ability to architect full-stack solutions.
Deep expertise in designing and implementing semantic layers, ontologies, and knowledge graphs for enterprise data systems.
Extensive experience with streaming architectures using Kafka, Spark Streaming, Flink, or similar technologies for data ingestion and processing.
Expert-level understanding of DevOps principles, with hands-on experience designing CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), and container orchestration (Kubernetes, EKS, AKS).
Significant experience with LLM-driven workflows, advanced prompt engineering, RAG (Retrieval-Augmented Generation) architectures, and orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI, AutoGen).
Deep familiarity with AI-powered development tools and practices, driving adoption of AI-augmented software development lifecycles across teams.
Experience with data governance frameworks, compliance standards (GDPR, CCPA), and enterprise security practices.
Published technical articles, conference presentations, or contributions to open-source projects in data engineering or related fields.
Key attributes
Strategic Thinking: Exceptional ability to balance tactical execution with long-term strategic vision, making architectural decisions that serve both immediate and future needs.
Technical Excellence: Deep technical expertise with a commitment to engineering excellence, code quality, and best practices.
Leadership & Influence: Proven ability to lead through influence, driving technical consensus across diverse stakeholders and organizational boundaries.
Ownership & Accountability: Strong executive presence with exceptional accountability for platform reliability, team performance, and business outcomes.
Collaboration & Communication: Outstanding interpersonal and communication skills, with ability to translate complex technical concepts for executive audiences and mentor engineers at all levels.
Innovation & Vision: Track record of identifying emerging technologies and driving their adoption to create competitive advantage.
Adaptability & Execution: Ability to operate effectively in ambiguous, fast-paced environments while maintaining high standards and delivering results.
Business Acumen: Strong understanding of business drivers, with ability to align technical investments with business value and ROI.
Location
On-site –Jalisco,MEX
If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements. We’re interested in getting to know you and what you bring to the table!
At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.
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Jones Lang LaSalle ("JLL") está comprometida a trabajar con personas con discapacidades y proporcionarles accesibilidad. Si necesita un ajuste razonable para cualquier parte del proceso de empleo – incluyendo la candidatura en línea y/o el proceso general de selección – puede enviarnos un correo electrónico a HRSCLeaves@jll.com. Este correo electrónico es solo para solicitar un ajuste razonable. Por favor, dirija cualquier otra consulta general de reclutamiento a nuestra página Contáctanos > Quiero trabajar para JLL.
