Data Analyst

JLL supports the Whole You, personally and professionally.

Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology to our clients. We are committed to hiring the best, most talented people in our industry; and we support them through professional growth, flexibility, and personalized benefits to manage life in and outside of work. Whether you’ve got deep experience in commercial real estate, skilled trades, and technology, or you’re looking to apply your relevant experience to a new industry, we empower you to shape a brighter way forward so you can thrive professionally and personally.

Data Analyst - Maternity Cover (6-10 months)Team: Data Team
Location: Hybrid
Reports to: Data Team Manager

About the RoleWe are seeking a detail-oriented Data Analyst to join our Data Team on a temporary basis to provide maternity cover. This is an excellent opportunity for a junior professional to gain hands-on experience working with complex real estate data pipelines in a dynamic Commercial Real Estate (CRE) environment, specifically on our Flowlogic system—a sophisticated data integration and transformation platform.

Key ResponsibilitiesMaintain and monitor existing data pipelines processing real estate data, including loans, property sales, acquisitions, and company hierarchies.

Integrate data from multiple real estate data sources to create unified, comprehensive datasets, ensuring accuracy across interconnected systems.

Execute complex data transformations using SQL within our proprietary Python-based framework for pipeline orchestration.

Monitor data quality, implement validation checks, and debug discrepancies across the pipeline to ensure data integrity.

Troubleshoot and resolve data processing issues, such as incorrect data mappings or validation failures, by analyzing data flows and transformation logic.

Collaborate closely with Product Managers and system users to understand data requirements and adapt to evolving needs.

Work with complex DAGs (Directed Acyclic Graphs) of data transformations, managing dependencies across hundreds of interconnected data tasks.

Technical RequirementsEssential: Strong SQL skills with the ability to write complex queries, including handling nested JSON structures and multi-layered joins.

Experience with Google BigQuery or similar cloud data platforms for large-scale data processing.

Basic Python knowledge (training on our proprietary Flowlogic framework for pipeline orchestration and dynamic SQL generation will be provided).

Understanding of data pipeline concepts and ETL processes, with a focus on data integration and transformation.

Experience with data quality monitoring, validation techniques, and debugging data discrepancies.

Familiarity with version control systems like Git for collaborative code and query management.

Key Qualities We're Looking ForSystems Thinking: Ability to understand and navigate complex, interconnected data transformation workflows, tracing data from raw inputs to final outputs.

Exceptional attention to detail and accuracy when handling intricate data mappings and validations.

Strong analytical mindset with problem-solving capabilities to address data pipeline issues.

Collaborative approach when working with cross-functional teams, including product and engineering staff.

Adaptability and eagerness to learn new tools, processes, and domain-specific real estate data concepts.

Preferred Qualifications1-3 years of experience in data analysis or data engineering roles.

Bachelor's degree in a quantitative field (Data Science, Computer Science, Mathematics, Statistics, or related).

Previous exposure to real estate data, such as company hierarchies or property transactions (not required but advantageous).

Experience with handling nested data formats (e.g., JSON) in SQL for data extraction and transformation.

What We OfferOpportunity to work with cutting-edge real estate data technology within the Flowlogic platform.

Flexible hybrid working arrangement to support work-life balance.

Exposure to a comprehensive CRE data ecosystem, handling diverse datasets and transformation challenges.

Mentorship and professional development opportunities to grow your skills in data analysis and pipeline engineering.

Please note: This is a temporary position covering maternity leave with an expected duration of 6-10 months.
If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements below. We’re interested in getting to know you and what you bring to the table!

Personalized benefits that support personal well-being and growth:

JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health.

About JLL –

We’re JLL—a leading professional services and investment management firm specializing in real estate. We have operations in over 80 countries and a workforce of over 102,000 individuals around the world who help real estate owners, occupiers and investors achieve their business ambitions. As a global Fortune 500 company, we also have an inherent responsibility to drive sustainability and corporate social responsibility. That’s why we’re committed to our purpose to shape the future of real estate for a better world. We’re using the most advanced technology to create rewarding opportunities, amazing spaces and sustainable real estate solutions for our clients, our people, and our communities.

Our core values of teamwork, ethics and excellence are also fundamental to everything we do and we’re honored to be recognized with awards for our success by organizations both globally and locally.

Creating a diverse and inclusive culture where we all feel welcomed, valued and empowered to achieve our full potential is important to who we are today and where we’re headed in the future. And we know that unique backgrounds, experiences and perspectives help us think bigger, spark innovation and succeed together.