Lead Data Engineer

Lead Data Engineer This position 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. Responsibilities 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 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. 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. Requirements Extensive experience with data pipeline orchestration tools (e.g., Apache Airflow, Luigi) and data integration platforms (e.g., Apache NiFi, Glue). Strong leadership and project management skills, with experience leading cross‑functional teams and managing multiple projects simultaneously. Expertise in cloud data platforms (AWS, Azure, GCP) 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, and AWS Lambda. Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. 7‑10 years of experience in data engineering, with significant leadership and project management experience. Exceptional ability to influence and engage senior leaders with data‑driven insights. Expertise in resolving complex, high‑stakes problems with innovative solutions. Experience with AWS, Snowflake, Azure, AWS Glue, AWS Appflow, Prefect, dbt, S3, Qlik SQL, Python, Java. Physical & Office/Site Presence Requirements This is an active position that requires the Senior Data Engineer to: Have the ability to work in excess of eight hours a day in the confined quarters of a construction trailer. Operate a motor vehicle, read plans, climb stairs, climb ladders, bend, stoop, reach, lift, move and/or carry equipment which may be in excess of 50 pounds. Operate computer equipment, see, speak, and hear. Have finger dexterity to operate an iPad and phone. Work outside in all weather conditions, around hazardous chemicals, dust, and dirt. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. #J-18808-Ljbffr