Jones Lang LaSalle (JLL) is a global leader in real estate services, dedicated to shaping the future of the real estate industry. JLL Technologies, its newly established Enterprise Data team, is spearheading the company's data strategy, driving innovation and efficiency in commercial real estate through cutting-edge data solutions.

The Data Engineer position at JLL is a key role within this team, responsible for designing and developing scalable data infrastructure using SQL and PySpark. This position offers the opportunity to collaborate with global teams, ensuring data requirements are met and high-quality data solutions are delivered. If you are ready to be a part of a dynamic environment where you can grow both professionally and personally, this guide by Interview Query will assist you in navigating the interview process and preparing for possible questions. Let’s begin!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining JLL as a Data Engineer. Whether you were contacted by a JLL recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the JLL Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the JLL Data Engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the JLL Data Engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around JLL’s data systems, ETL pipelines, SQL, and tools like Snowflake and PySpark.

Depending on the specific interviewer's focus, you might face questions around variables that should be considered for predicting house prices or solving SQL queries to find the highest salary. Proficiency in tools like SQL and PySpark will be crucial for this round.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the JLL office. Your technical prowess, including cloud-based data infrastructure, data pipeline frameworks, and collaboration with cross-functional teams, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Engineer role at JLL.

Quick Tips For JLL Data Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your JLL interview include:

• Brush Up on SQL and PySpark Skills: JLL’s Data Engineer interviews heavily focus on SQL and PySpark. Make sure you are well-versed with these tools, including cloud platforms and data pipeline frameworks.
• Understanding Data Warehousing: Questions may include practical scenarios on cloud data warehousing platforms like AWS Redshift, Google BigQuery, or Snowflake. So, ensure you have a solid understanding of these.
• Demonstrate Problem-Solving Skills: Be prepared to resolve complex data processing issues and understand JLL's data requirements. Communication and problem-solving skills are crucial for acing the interview.

Typically, interviews at JLL vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• What considerations should be made when testing hundreds of hypotheses with many t-tests? When conducting multiple t-tests, you need to consider the risk of Type I errors (false positives) due to multiple comparisons. Implement corrections like the Bonferroni correction or False Discovery Rate (FDR) to control for this risk.

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates multiple decision trees and why it might be preferred over logistic regression for certain tasks.

• How do we handle missing square footage data in Seattle housing price model? You have 100K sold listings with 20% missing square footage data. Describe methods to handle this missing data to construct a predictive model.

• How would you combat overfitting in tree-based classification models? When training a classification model, explain strategies to prevent overfitting, particularly in tree-based models.

• Does increasing the number of trees in a random forest always improve accuracy? Discuss whether sequentially increasing the number of trees in a random forest model will continuously improve its accuracy.

• How to implement k-means clustering algorithm in Python from scratch? Given a two-dimensional NumPy array data_points, number of clusters k, and initial centroids, write a Python function to perform k-means clustering and return the cluster assignment for each data point.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background.

• How should you handle a right-skewed distribution when predicting real estate home prices? You are building a model to predict home prices in a city and notice the prices are right-skewed. Should you take any action? If so, what steps should you take?

• Bonus: How should you handle a left-skewed target distribution? If the target distribution is heavily left-skewed, what actions should you take?

What is the average salary for a Data Engineer at Jll?

Q: What is JLL's interview process like for a Data Engineer position?

A: The interview process at JLL for a Data Engineer role typically involves a recruiter call, followed by technical interviews that focus on SQL, Snowflake, and general data engineering concepts. Be prepared for questions related to cloud-based data infrastructure, PySpark, and collaboration with cross-functional teams. Feedback may not always be prompt, so patience is key.

Q: What skills and qualifications are JLL looking for in a Data Engineer?

A: JLL seeks candidates with a Bachelor's degree in Computer Science, Data Engineering, or a related field, and at least 3 years of experience. Proficiency in SQL, PySpark, and cloud platforms like AWS, Azure, or GCP is crucial. They value strong problem-solving skills, experience in data pipeline development, and effective communication abilities.

Q: What is the company culture like at JLL?

A: JLL supports the "Whole You," both personally and professionally. The company fosters a supportive culture emphasizing professional growth, flexibility, and personalized benefits. JLL values diversity, innovation, and collaboration, aiming to shape the future of real estate through world-class services, advisory, and technology.

Q: How can I prepare for an interview at JLL?

A: To prepare for a JLL interview, focus on strengthening your technical skills in SQL, PySpark, and cloud platforms. Understanding data warehousing concepts, ETL processes, and modern data engineering practices is essential. Use Interview Query to practice and get comfortable with potential technical and behavioral questions.

Q: What are the benefits of working at JLL?

A: JLL offers a comprehensive benefits package prioritizing mental, physical, and emotional health. Benefits include a 401(k) plan with matching contributions, comprehensive medical, dental, and vision care, paid parental leave, flexible work arrangements, and more. The company aims to support your well-being in and out of the workplace.

If you want more insights about the company, check out our main JLL Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about JLL’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every JLL Data Engineer interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!