Data Engineer

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Jones Lang LaSalle Americas, Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

We provide commercial real estate services for corporations and investors across the globe that save money, increase productivity and improve sustainability.

📋 Description

• Support the development of information infrastructure and data management processes as JLL moves toward a more sophisticated, agile, and robust target state data architecture • Assist in building systems that ingest, cleanse, and normalize diverse datasets, contribute to data pipelines from various internal and external sources, and help structure previously unstructured data • Learn and apply modern data architecture approaches under the guidance of senior engineers to help meet key business objectives and contribute to end-to-end data solutions • Develop an understanding of how data flows and is stored across multiple enterprise applications such as CRM, Broker & Sales tools, Finance, and HR systems • Support the development of data management and data persistence solutions for application use cases, leveraging both relational and non-relational databases • Participate in code reviews, documentation, and knowledge sharing activities to grow your technical expertise and contribute to team best practices

🎯 Requirements

• 0–2 years’ overall work experience and a Bachelor’s degree (or in progress) in Information Science, Computer Science, Mathematics, Statistics, or a quantitative discipline in science, business, or social science • Foundational knowledge of Python and SQL; exposure to data engineering tools such as Spark, Kafka, or cloud storage platforms is a plus • Familiarity with Azure cloud services such as Azure SQL Server, Azure Data Lake Storage, Cosmos DB/MongoDB, or Azure Event Hubs is advantageous but not required • Awareness of data pipeline concepts, data lake environments, and event-driven architectures; willingness to learn and apply these in a hands-on setting • Experience or coursework involving data processing, ETL workflows, or working with structured and unstructured data will be an advantage • A collaborative team player who is reliable, self-motivated, and capable of contributing within a fast-paced environment working across cross-functional teams

🏖️ Benefits

• Total Rewards program reflecting commitment to employee ambitions in career, recognition, well-being, benefits and pay