Data Engineer | Talent Community

Lennar is one of the nation's leading homebuilders and a Fortune 500® company with a growing technology organization focused on innovation, data, digital experiences, and technology that helps shape the future of homebuilding.

Data is at the center of that transformation. We're investing in modern data platforms and engineering capabilities that enable better decisions, smarter products, greater operational efficiency, and new ways of using data across the organization.

We're always looking to connect with talented Data Engineers who are excited about building the platforms and products that turn data into something our teams can use to make better decisions.

This is a proactive talent community opportunity for Data Engineers interested in exploring future opportunities with Lennar. While we may not have an immediate opening that matches your background, we'd like to get to know you and stay connected as our Enterprise Data & Analytics organization continues to grow.

Whether your expertise is in data platforms, data pipelines, cloud data engineering, data architecture, data integration, streaming, analytics engineering, or another area of data engineering, we welcome the opportunity to learn more about your experience and career interests.

• Design, build, and operationalize scalable data engineering solutions for Lennar's data platforms and products.
• Build and optimize ETL and ELT pipelines that bring together data from diverse sources.
• Develop data ingestion and integration solutions using batch, incremental, change data capture (CDC), streaming, and API-based approaches.
• Design and implement data models, data warehouses, data lakes, and modern cloud data platforms.
• Build reliable, reusable, and maintainable data transformation processes that enable analysts, data scientists, and business teams to work with trusted data.
• Improve data quality, reliability, observability, monitoring, and error handling across data pipelines and platforms.
• Develop automated testing, CI/CD workflows, version control practices, and other engineering standards that improve the quality and speed of delivery.
• Partner with data analysts, data scientists, product teams, software engineers, and business stakeholders to understand requirements and deliver data solutions that support real business outcomes.
• Help create self-service data capabilities that make it easier for teams across Lennar to access and use data.
• Contribute to data governance, security, compliance, and access-control practices.
• Troubleshoot complex data and platform issues and identify opportunities to improve performance, scalability, and maintainability.
• Stay current with emerging data technologies and engineering practices and help identify opportunities to apply them at Lennar.

Our data environment continues to evolve, and future opportunities may span a variety of technologies, platforms, and architectural approaches.

Depending on the role and team, experience with technologies such as the following may be relevant:

• AWS, including services such as S3, EMR, Glue, Lambda, EKS, EC2, and Cloud Watch
• Snowflake and modern cloud data warehouse technologies
• dbt and modern analytics engineering practices
• SQL and Python
• ETL/ELT, data ingestion, CDC, REST APIs, and streaming
• Airflow, Prefect, or other orchestration and scheduling technologies
• Git Hub, CI/CD, automated testing, and modern software development practices
• Data modeling, data warehousing, data lakes, and data architecture
• Data governance, security, access controls, and data quality
• Data replication and integration technologies such as Qlik Replicate

You don't need experience with every technology listed. We're interested in understanding the data challenges you've solved, the platforms you've built, and the technologies you're excited to work with next.

We're interested in connecting with Data Engineers across a range of experience levels and specialties who bring:

• Professional experience designing, developing, and supporting data pipelines, platforms, products, or related engineering solutions.
• Strong understanding of data engineering fundamentals, including data modeling, transformation, ingestion, testing, monitoring, and data quality.
• Strong SQL skills and experience with one or more programming languages, such as Python.
• Experience working with cloud-based data platforms and…