Principal Data Engineer

Principal Data Engineer Overview Lennar is a Fortune 500® homebuilder committed to building quality homes and fostering growth. The Principal Data Engineer will help transform the organization into a data, insights, and AI-driven enterprise. Your Responsibilities on the Team Design, build, and operationalize data engineering solutions across Lennar’s bronze, silver, and gold data layers, ensuring the platform is reliable, scalable, and trusted as the foundation for analytics and AI initiatives.

Lead architecture decisions for pipeline frameworks, orchestration patterns, and cloud data storage strategies including Apache Iceberg and S3, with a focus on making data AI-ready across the enterprise. Architect and implement ETL, ELT, and streaming data ingestion and delivery processes across multiple enterprise source systems including JDE and Salesforce. Define and implement standards and best practices for the data engineering team, including code modularization, versioning, testing, CI/CD automation, and code reviews.

Instrument data platforms with robust metrics, observability, and monitoring to support operational reliability and data quality commitments. Collaborate with cloud engineering, data governance, and MDM teams to ensure platform architecture supports lineage, compliance, and master data requirements. Serve as a primary technical escalation point for complex platform issues, degradations, and production incidents.

Mentor and develop data engineers across the team through design reviews, code reviews, and hands‑on pairing — helping Associates grow their skills and solve problems they haven’t encountered before. Represent the Data & AI Platforms team in cross‑functional technical discussions with Salesforce, JDE, cloud engineering, and AI product teams. Evaluate and introduce new technologies and architectural patterns — including emerging AI and data infrastructure tooling — through prototyping, benchmarking, and structured recommendation.

Gain a deep understanding of Lennar’s core business processes and align platform development with business strategy and AI adoption goals. Technical Requirements Expertise (At least 8+, prefers 12+ years) in: Data architecture design and data platform engineering Data modeling, cloud data warehousing, and lakehouse concepts Data transformation, standardization, and medallion layer design ETL/ELT processes, strategies, and pipeline reliability patterns Monitoring, observability, and error handling for data systems SDLC, workflow best practices, code reviews, and QA/testing methodologies Strong experience (At least 3+, prefers 6+ years) with the following technologies and platforms: AWS data services: S3, Glue, Athena, MWAA (Airflow), Kafka (MSK), Lambda, EMR, CloudWatch; AWS certification a plus Snowflake Data Cloud: account administration, virtual warehouse strategies, role‑based access control, Data Sharing, Time Travel, and Zero‑copy cloning dbt: managing multi‑repository projects, authoring and maintaining models, macros, incremental strategies, testing frameworks, and semantic layer development Apache Iceberg and lakehouse table format patterns Version control and branching strategies (GitHub a plus) Proficiency in SQL and Python Data governance, security, and compliance concepts Incremental and CDC ingestion methods; REST APIs Familiarity (At least 1+ years of experience) with: Orchestration and scheduling tools (Airflow / MWAA preferred) Qlik Replicate for data ingestion and CDC pipeline delivery Data lineage and observability tooling (OpenLineage / Marquez or similar) Data quality and MDM platforms (Ataccama, Reltio, or similar) AI/ML platform concepts, including feature stores, vector data, or model data pipelines Other Requirements Ability to work collaboratively and productively with other team members to achieve Lennar’s objectives. Demonstrated experience across all aspects of development including requirements gathering, technical design, implementation, testing, and post-implementation support.

Ability to partner with business users, stakeholders, and AI product teams to gather solution requirements and deliver data that enables their work. Strong communication skills — able to convey technical complexity clearly to non-technical stakeholders and leadership. Genuine enthusiasm for AI and its potential to transform how a large enterprise operates — and a desire to build the data infrastructure that makes it possible.

Thirst to help transform Lennar into an insights‑and‑AI‑driven organization. Ability and willingness to quickly learn new technologies and grow with the platform. Ability and willingness to learn about the business, its strategy, objectives, and core business processes.

Additional Requirements Travel up to 10% of the time to Divisions within the Lennar family. Interact well with co‑workers. Cross‑train for position(s) within the team organizational structure from time to time, as required by the Leadership Team.

Comply with and implement company policies and procedures. Accept constructive criticism. Strong work ethic.

Team player. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. #J-18808-Ljbffr