Senior Data Engineer

JLL empowers you to shape a brighter way.

Our people at JLL are shaping the future of real estate for a better world by combining world class services advisory and technology for our clients. We are committed to hiring the best most talented peopleand empowering them to thrive grow meaningful careers and to find a place where they belong. Whether youve got deep experience in commercial real estate skilled trades or technology or youre looking to apply your relevant experience to a new industry join our team as we help shape a brighter way forward.

About Us

JLL (NYSE: JLL) is a Fortune 500 leader in commercial real estate services operating globally with annual revenue in the tens of billions. Within JLL Technologies our strategic business unit we harness cutting-edge technology to unlock value and enhance liquidity across the worlds built environment.

Our Tel Aviv technology hub drives enterprise-scale AI data science and machine learning initiatives that power JLLs multi-billion-dollar business. We design build and operate production-grade data and AI systems that inform critical decisions across the organization.

About the Role

Were seeking a Senior Data Engineer to spearhead the modernization of our core data platform. Youll lead the evolution of our large-scale cloud-based data infrastructuremigrating to a modern Lakehouse architecture streamlining operations and establishing best-in-class data quality and observability practices. Youll also explore AI-assisted data collection methods and help architect secure governed access patterns for internal tools and intelligent agents.

This is a hands-on role offering genuine ownership: youll shape architecture drive implementation and collaborate closely with engineering and product teams to define what an exceptional data infrastructure looks like.

This position offers flexible hybrid working arrangements.

What Youll Do

1. Modernize the data platform

• Lead migration from our current warehouse and orchestration setup to Databricks creating a clear transformation roadmap

• Redesign pipeline architecture to improve operational efficiency and maintainability

• Build observable repeatable orchestrated workflows that are easier to own and operate

• Refactor data structures into cleaner relational models that enhance maintainability testability and lineagewhile ensuring seamless transitions for downstream consumers

• Create comprehensive documentation including migration patterns phased rollout plans and operational runbooks

2. Establish data quality excellence

• Design and implement a robust data quality framework across critical datasets using industry-standard tools

• Build automated checks for schema validation volume monitoring freshness tracking and distribution analysis

• Explore agent-assisted validation for complex scenarios incorporating human review where judgment is needed

• Create actionable alerting with clear ownership so teams can respond confidently to issues

• Partner with domain experts to translate business requirements into durable automated validation

3. Enable secure governed data access

• Architect how internal users and AI agents access curated data safely through protocols like MCP (Model Context Protocol) with proper authentication scoping and auditability

• Prototype integrations between the lakehouse and tools engineers and analysts use daily

• Help shape our data as a product strategy with appropriate access boundaries and governance

What Were Looking For

Required Experience

• 5 years in data engineering with end-to-end ownership of production pipelines

• Strong proficiency in Spark and distributed processing

• Expert-level SQL and experience designing effective warehouse/lakehouse data models

• Advanced Python skills for building data infrastructure: factory patterns abstractions dynamic DAG generation from configuration parameterized task definitions and other programmatic orchestration patternsnot just scripting

• Proven track record building or migrating complex batch pipelines including dependency mapping phased migration strategies and maintaining backward compatibility

• Practical experience implementing data quality frameworks building custom tests establishing monitoring and responding effectively when issues arise

• Excellent communication skills with both technical and business stakeholders

Strong Advantages

• Experience with web scraping or API ingestion at scale; curiosity about LLM/agent approaches for data extraction and pipeline maintenance

• Familiarity with MCP LLM tool integration or internal data agent prototypes with appropriate guardrails

• Background working with complex domain data including hierarchies entities or transactional systems
• Strong proficiency with Databricks (jobs/workflows catalog/governance Delta or similar formats)

Location:

If this job description resonates with you we encourage you to apply even if you dont meet all of the requirements. Were 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 yourepursuing.

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Jones Lang LaSalle (JLL) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process including the online application and/or overall selection process you may email us at . This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.