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Role summary:
As a Data Engineer, you will lead the development of scalable data pipelines and integration of diverse data sources into the JLL Asset Beacon platform.
Your work will focus on consolidating financial, operational, and leasing data into a unified platform that delivers accurate insights for commercial real estate asset management. Collaborating closely with internal developers and stakeholders, you will gather requirements, solve integration challenges, and ensure seamless data flows to support informed decision-making.
In addition to technical responsibilities, you will mentor junior engineers, promote best practices in data engineering and maintain high-quality standards through code reviews. Leveraging tools like Spark, Airflow, Kubernetes, and Azure, you will enhance the platform's performance, reliability, and scalability. Your expertise in data ecosystems will play a critical role in driving innovation and enabling advanced data-driven solutions for the evolving needs of the real estate industry.
Company bio:
JLL Asset Beacon is transforming commercial real estate asset management through data integration and innovation. Our SaaS platform consolidates and reconciles data across financial, operational, and leasing functions, creating a single source of truth. By providing real-time, end-to-end visibility into asset, fund, and portfolio performance, we empower real estate professionals to make faster, more informed decisions. With robust data visualization and reporting capabilities, our platform simplifies complex data ecosystems, enabling seamless collaboration and unlocking opportunities for value creation.
Responsibilities:
- Data pipeline development
- Design and implement scalable, efficient, and robust data pipelines
- Data platform management
- Support and main the data platform to ensure reliability, security, and scalability.
- Collaborate with internal developers and stakeholders
- Work closely with internal developers and stakeholders to gather requirements, deliver insights, and align project goals.
- Mentorship and leadership
- Mentor junior engineers, fostering their growth through knowledge sharing and guidance
- Conduct code reviews to maintain quality and consistency
Our Technologies:
- Data Processing: Spark
- Workflow Orchestration: Airflow
- Containerization: Kubernetes
- Cloud: Azure
- Data APIs and Semantic Layer: CubeJS
The Candidate:
- Educational Background: A STEM degree, preferably in Computer Science or Computing.
- Professional Experience: At least 2 years of experience in data engineering, data warehousing, or a related field.
Technical Proficiency:
- Strong Python and PySpark experience
- SQL skills are essential
- Experience with data orchestration platforms or tools such as Airflow, ADF, or SSIS
Data Expertise:
- Solid understanding of data modeling principles and data warehousing concepts.
Domain Knowledge:
- Financial or real estate experience is advantageous but not required.
Location:
On-site –Bristol, GBRIf this job description resonates with you, we encourage you to apply, even if you don’t meet all the requirements. We’re interested in getting to know you and what you bring to the table! If you require any changes to the application process, please email [email protected] or call +44 (0)20 7493 4933 to contact one of our team members to discuss how to best support you throughout the process. Please note, the contact details provided are to discuss or request for adjustments to be made to the hiring process. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.
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