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 Lead Data Engineer is responsible for overseeing the data engineering team and driving the strategic direction of data initiatives. The role involves managing projects, ensuring the scalability of data solutions, and collaborating with stakeholders to meet organizational goals. 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 Lead and manage the data engineering team, including project planning, resource allocation, and performance management. Develop and enforce data engineering standards, processes, and best practices, ensuring consistency and quality across all data projects. Collaborate with stakeholders, including business leaders, data scientists, and IT teams, to understand and prioritize data-related business needs and translate them into actionable technical requirements. Ensure data solutions are scalable, secure, and aligned with the long-term goals of the organization, considering both current and future data needs. Drive the adoption of new technologies, tools, and methodologies that improve the efficiency, reliability, and scalability of data engineering practices. Oversee the development and maintenance of comprehensive data documentation, including data architecture diagrams, process flows, and technical specifications. Manage the team's technical debt, ensuring that legacy systems are modernized and that new solutions are built with maintainability and scalability in mind. Provide technical leadership in the resolution of complex data issues, guiding the team in troubleshooting and problem-solving efforts. Knowledge Extensive experience with data pipeline orchestration tools (e.g., Apache Airflow, Prefect) and data integration platforms (e.g., Apache Spark, Glue). Extensive experience working on AWS data stack i.e., Data engineering, Warehousing and AI/ML. Advocate best practices with AWS including Glue, EMR, Airflow and etc., Strong leadership and project management skills, with experience leading cross-functional teams and managing multiple projects simultaneously. Expertise in cloud data platforms (AWS, Azure) and big data ecosystems, with a focus on optimizing cost, performance, and scalability. Proficient in advanced data modeling, including the design of enterprise data warehouses, data lakes, and data marts. In-depth knowledge of data governance practices, including data cataloging, data lineage, and data quality management. Experience with enterprise data management frameworks, such as Master Data Management (MDM) and metadata management. Advanced skills in programming and scripting languages (e.g., Python, Java, Scala) for developing and automating data workflows. Experience with real-time data processing and event-driven architectures, leveraging tools such as Apache Kafka, Spark Streaming.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees