Data Engineer Tech Lead

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Our people at JLL and JLL Technologies 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.   

We are seeking a Data Engineer Tech Lead to join our capital markets data engineering teams, focusing on designing, building, and maintaining scalable data infrastructure on the Databricks platform. This role requires deep technical expertise in modern data stack technologies and the ability to work with complex financial data systems.

Technical Development

• Design and implement robust, scalable data pipelines using Databricks, Apache Spark, and Delta Lake as well as BigQuery
• Use SQL and Python to develop, scale, and optimize advanced data pipelines. 
• Build and optimize ETL/ELT processes for capital markets data i
• Develop real-time and batch processing solutions to support trading and risk management operations
• Implement data quality monitoring, validation, and alerting systems

Platform Engineering

• 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

Collaboration & Mentorship

• Collaborate with various stakeholders across the company and support business insight requests. 
• Work closely with quantitative researchers, risk analysts, and product teams to understand data requirements
• Collaborate with other data engineering teams and infrastructure groups
• Provide technical guidance to junior engineers and contribute to code reviews
• Participate in architecture discussions and technology selection decisions

• Engineering experience with strong expertise in Apache Spark and distributed computing
• Strong programming skills in Python including data handling libraries (pandas, numpy, etc.), and data modeling. 
• Proficient in Databricks platform and Delta Lake for data lake architecture
• Proficient in writing complex SQL queries,
• Experience with cloud-based databases (Google BigQuery \ Snowflake) .
• Advanced SQL skills and experience with both relational and NoSQL databases
• Bachelor's degree in Computer Science, Engineering or related field
• Experience with integration of multiple data sources and working with various databases technologies. 

• Experience with Azure cloud platform and associated data services (Data Factory, Event Hubs, Storage)
• Experience with EKS / AKS
• Knowledge of data streaming platforms (Kafka, Azure Event Hubs) for real-time processing
• Experience working in a multi cloud environment

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If 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!

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