Principal Data Engineer

Principal Data Engineer

The primary mission of the Principal Data Engineer role is to help our business evolve into a data, insights, and AI‑driven organization. This position sits in our Data and AI team, which aims to drive improved business outcomes using insights and intelligence gleaned from data, infusing them into Lennar’s corporate fabric.

The Principal Data Engineer is a senior individual contributor who brings deep technical expertise across data platform engineering and data architecture. As AI becomes central to how Lennar operates, this role is foundational—the data platform this person builds and maintains is what makes enterprise AI possible. The Principal Data Engineer shapes how data moves through Lennar’s enterprise systems, sets the engineering standards the team builds against, and actively elevates the engineers around them through mentorship, architecture guidance, and hands‑on collaboration.

The Principal Data Engineer is a key role in maturing and scaling Lennar’s enterprise data fabric to support both analytics and AI at scale.

• 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.

• 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

• AWS data services: S3, Glue, Athena, MWAA (Airflow), Kafka (MSK), Lambda, EMR, Cloud Watch; 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 / semantic model development
• Apache Iceberg and lakehouse table format patterns
• Version control and branching strategies (Git Hub a plus)
• Proficiency in SQL and Python
• Data governance, security, and compliance concepts
• Incremental and CDC ingestion methods; REST APIs

• Orchestration and scheduling tools (Airflow / MWAA preferred)
• Qlik Replicate for data ingestion and CDC pipeline delivery
• Data lineage…