Senior Data Engineer
WFA Digital Insight
The demand for skilled data engineers has skyrocketed in recent years, with a notable 25% increase in job postings in 2025 alone. As companies like JLL continue to invest in digital transformation, professionals with expertise in big data technologies are in high demand. With its commitment to innovation and employee growth, JLL stands out as an attractive employer in the industry. Before applying, candidates should be prepared to showcase their technical skills, particularly in managing large-scale data projects and collaborating with cross-functional teams.
Job Description
About the Role
The Senior Data Engineer role at JLL is a critical position that involves designing and developing data solutions that are strategic to the business. As part of the Capital Markets Data Engineering team, this individual contributor role requires a self-starter who can work in a diverse and fast-paced environment. The successful candidate will have the opportunity to leverage the latest technologies and patterns to deliver high-quality data solutions.The role is part of JLL Technologies, a specialized group within JLL that delivers unparalleled digital advisory, implementation, and services solutions to organizations globally. The team's goal is to leverage technology to increase the value and liquidity of the world's buildings while enhancing the productivity and happiness of those who occupy them.
As a Senior Data Engineer, you will be responsible for partnering with the broader JLL T team at the country, regional, and global levels, utilizing in-depth knowledge of data, infrastructure, technologies, and data engineering experience.
What You Will Do
- Design and implement robust, scalable data pipelines using Databricks, Apache Spark, and Delta Lake as well as BigQuery
- Design and implement efficient data pipeline frameworks, ensuring the smooth flow of data from various sources to data lakes, data warehouses, and analytical platforms
- Troubleshoot and resolve issues related to data processing, data quality, and data pipeline performance
- Document data infrastructure, data pipelines, and ETL processes, ensuring knowledge transfer and smooth handovers
- Create automated tests and integrate them into testing frameworks
- Configure and optimize Databricks workspaces, clusters, and job scheduling
- Work in a Multi-cloud environment including Azure, GCP, and AWS
- Implement security best practices including access controls, encryption, and audit logging
- Build integrations with market data vendors, trading systems, and risk management platforms
- Establish monitoring and performance tuning for data pipeline health and efficiency
- Collaborate with cross-functional teams to understand data requirements, identify potential data sources, and define data ingestion
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet their needs
What We Are Looking For
- Bachelor's degree in Computer Science, Data Engineering, or a related field (Master's degree preferred)
- Minimum 5+ years of experience in data engineering or full-stack development, with a focus on cloud-based environments
- Advanced expertise in managing big data technologies (Python, SQL, PySpark, Spark) with a proven track record of working on large-scale data projects
- Strong Databricks experience
- Advanced database/backend testing with the ability to write complex SQL queries
- Excellent communication and collaboration skills
- Ability to work in a fast-paced environment and prioritize multiple tasks
Nice to Have
- Experience with cloud-based data platforms such as AWS, Azure, or GCP
- Knowledge of data governance and data quality best practices
- Familiarity with agile development methodologies
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work with a leading global company
- Collaborative and dynamic work environment
- Professional development and growth opportunities
- Flexible working hours and remote work options
- Access to cutting-edge technologies and tools
- Recognition and reward for outstanding performance
How to Stand Out
- Make sure to highlight your experience with big data technologies such as Databricks, Apache Spark, and Delta Lake in your resume and cover letter.
- Showcase your ability to work in a fast-paced environment and prioritize multiple tasks by providing specific examples from your previous experience.
- Prepare to answer technical questions related to data engineering, such as data pipeline design and optimization, during the interview process.
- Emphasize your excellent communication and collaboration skills, as they are essential for success in this role.
- Be prepared to discuss your experience with cloud-based data platforms and data governance best practices.
- Consider creating a portfolio that demonstrates your data engineering skills and experience, such as designing and implementing data pipelines or optimizing data warehouse performance.
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