At a Glance
- Tasks: Lead the development of scalable data pipelines and integrate diverse data sources.
- Company: Join JLL, a leader in transforming commercial real estate through innovation.
- Benefits: Empowering culture, career growth, and opportunities to make a real impact.
- Other info: Mentorship opportunities and a dynamic work environment in Bristol.
- Why this job: Shape the future of real estate with cutting-edge technology and data solutions.
- Qualifications: 5+ years in data engineering, strong Python skills, and a STEM degree.
The predicted salary is between 49500 - 60500 £ per year.
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 people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.
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.
Responsibilities:
- Data pipeline development: Design and implement scalable, efficient, and robust data pipelines.
- Data platform management: Support and maintain 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 5 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, GBR
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!
Data Engineer in Bristol employer: Jones Lang Lasalle
At JLL, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters collaboration and innovation. Our commitment to employee growth is evident through tailored career development opportunities and the chance to work alongside industry experts in the heart of Birmingham and London. Join us to be part of a forward-thinking team that values your contributions and empowers you to make a meaningful impact in the real estate sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Bristol
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jones Lang Lasalle.
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We think you need these skills to ace Data Engineer in Bristol
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Jones Lang Lasalle, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jones Lang Lasalle. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Jones Lang Lasalle
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jones Lang Lasalle!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
