Principal Data Engineer

Lennar•Waterford, FL

6d•Onsite

About The Position

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. 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.

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 / semantic model 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
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.
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.

Responsibilities

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.