Lennar · Irving, TX (job Posting Location)Prepare for this interview
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Lead Data Engineer We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States. Join a Company that Empowers you to Build your Future The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. This position sits in our Enterprise Data and Analytics team, which aims to drive improved business outcomes using insights gleaned from data and analytics, infusing them into Lennar's corporate fabric. The Lead Data Engineer will provide technical leadership to our data platform engineering team. This is done by helping design and implement our next generation data and analytics platforms and products using Data engineering best practices. The Lead Data Engineer also will implementing engineering solutions along with the team. In addition, this person focuses on empowering and enabling our business users through self-service and automation. The Lead Data Engineer is a key role in operationalizing Lennar's enterprise data fabric. A career with purpose. A career built on making dreams come true. A career built on building zero defect homes, cost management, and adherence to schedules. Your Responsibilities on the Team Design, build, and operationalize data engineering solutions for Lennar's data and analytics platforms and products. Architect and implement ETL, ELT and streaming data ingestion data delivery processes across multiple sources. Experience in data modeling, cloud data lake, cloud data warehouse Instrument data analytics platforms with robust metrics and monitoring. Improve data ingestion architecture, emphasizing data quality, maintainability, and extensibility. Support process improvement on the team to enable rapid development of data products. Define and Implement standards and best practices for data analytics team, including code modularization, versioning, testing, automation of CI/CD workflows, code reviews etc. Gain an understanding of core business processes and align data development with business strategy. Wrangle and integrate data from disparate systems to allow data analysts and data scientists to leverage end-to-end data and information.
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