Data Engineer

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🕒 June 3

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Jones Lang LaSalle Americas, Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

We provide commercial real estate services for corporations and investors across the globe that save money, increase productivity and improve sustainability.

📋 Description

• 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.

🎯 Requirements

• Bachelor's degree in Computer Science, Data Engineering, or a related field (Master's degree preferred) • Minimum 3-5 years of experience in data engineering or full-stack development, with a focus on cloud-based environments • Strong expertise in managing big data technologies (Python, SQL, PySpark, Spark) • Proven track record of working on large-scale data projects • Strong Databricks experience • Strong database/backend testing with the ability to write complex SQL queries for data validation and integrity • Strong experience in designing and implementing data pipelines, ETL processes, and workflow automation • Familiarity with data warehousing concepts, dimensional modeling, data governance best practices, and cloud-based data warehousing platforms (e.g., Google BigQuery, Snowflake) • Experience with cloud platforms such as Microsoft Azure, or Google Cloud Platform (GCP) • Experience working in DevOps model • Experience with Unit, Functional, Integration, User Acceptance, System, and Security testing of data pipelines.

🏖️ Benefits

• JLL as a company is committed to equal opportunities for men and women. • opportunities to advance your career from within. • explore opportunities to advance your career from within.