Quality Data Analyst

JLL•Chicago, IL

1d•Onsite

About The Position

As a Quality Data Analyst at JLL, you will play a key role in safeguarding the accuracy, consistency, and reliability of JLL’s enterprise data assets. This role focuses on executing data stewardship and data quality initiatives that support informed business decisions across the organization. You will enrich, validate, and monitor company, property, and contact data using a combination of proprietary platforms, cloud-based technologies, and external data sources. By partnering closely with cross-functional stakeholders, you will help strengthen JLL’s data foundation while contributing to a collaborative, high-impact data culture that supports our clients and internal teams globally.

Requirements

Bachelor’s degree in Business, Finance, Information Science, Computer Science, Data Science, Mathematics, Statistics, or a related field.
Strong SQL skills, including experience with joins, subqueries, and data manipulation statements.
Advanced Microsoft Excel proficiency, including pivot tables and lookup functions.
Proven experience working with large datasets and supporting data quality or data management initiatives.
Strong analytical, problem-solving, and attention-to-detail skills.
Excellent communication and documentation skills, with the ability to translate business requirements into technical outcomes.

Nice To Haves

Experience with Azure Databricks, cloud-based data platforms, or Google Cloud Platform tools.
1–3 years of experience in data analysis, data management, or data stewardship roles.
Knowledge of data governance frameworks, best practices, and Master Data Management concepts.
Experience using business intelligence or reporting tools such as Power BI or Tableau.
Familiarity with API integrations, data pipelines, and automated data quality solutions.
Exposure to commercial real estate, corporate real estate, consulting, or cross-functional project environments.

Responsibilities

Execute data stewardship activities to enrich, validate, and maintain company, property, and contact data across enterprise systems.
Design, implement, and maintain data quality rules, validation checks, and monitoring processes.
Write and optimize intermediate to advanced SQL queries for data extraction, transformation, and analysis.
Use Azure Databricks and Python to perform large-scale data processing, profiling, and automated data quality checks.
Perform data profiling, cleansing, and standardization to improve overall data integrity.
Collaborate with cross-functional teams to identify, troubleshoot, and resolve data quality issues, following established escalation procedures.
Document data lineage, quality metrics, and stewardship processes, and communicate insights to technical and non-technical stakeholders.