Lead Data Engineer

Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates. The Lead Data Engineer role focuses on providing technical leadership to the Product Team by designing and implementing data and analytics platforms and products, as well as empowering business users through self-service and automation.

Responsibilities:

• Formulate production-grade data engineering solutions for Lennar’s data and analytics platforms and products
• Architect and implement reliable ETL, ELT, and streaming data ingestion/delivery processes across multiple enterprise sources
• Develop, maintain, and containerize modular data applications and utility scripts using Python, leveraging modern cloud infrastructure
• Improve data ingestion architecture, emphasizing data quality, cost-performance, maintainability, and extensibility across storage and compute layers
• Define and implement engineering standards for the data team (including code modularization, version control, automated testing, and secure CI/CD workflows). Ensure strict guidelines for schema evolution to safeguard downstream analytics from unilateral changes
• Instrument data analytics platforms with robust metrics, alerting, and automated monitoring (SLAs/SLOs) to ensure high availability and data trustworthiness
• Leverage modern AI-assisted development tools within daily engineering workflows to accelerate code generation, optimize heavy queries, and improve overall delivery speed
• Collaborate with data science teams to design and optimize data layers specifically tailored for Generative AI applications, Retrieval-Augmented Generation (RAG), and LLM frameworks
• Wrangle and integrate data from highly disparate production systems to allow data analysts and data scientists to leverage optimized, end-to-end data products
• Gain a deep understanding of core business processes and align technical data development with strategic business objectives

Requirements:

• Core Expertise (8+ years preferred) in Data Architecture & Enterprise Modeling: Advanced data warehousing concepts, cloud data lakes, and structured multi-layer designs (Bronze, Silver, Gold)
• Core Expertise (8+ years preferred) in Advanced Data Transformations: Designing complex operational pipelines, data cleanup, and robust standardization strategies
• Core Expertise (8+ years preferred) in Production SDLC & Workflow Best Practices: Rigorous code reviews, end-to-end testing/QA methodologies, and resilient error-handling frameworks
• Core Expertise (8+ years preferred) in Data Governance & Security: Implementing enterprise-level role-based access controls (RBAC), data compliance, and secure environments
• Strong Technical Experience (3+ to 6+ years) with Advanced Python Development: Writing clean, object-oriented, and production-grade Python code for complex data manipulation, automation, and API communication
• Strong Technical Experience (3+ to 6+ years) with AWS Platform & Containerization: Hands-on experience deploying, managing, and scaling containerized data workloads using AWS ECS (Elastic Container Service) and ECR
• Strong Technical Experience (3+ to 6+ years) with AWS Platform & Containerization: Core AWS architecture: S3, IAM, Lambda, EC2, CloudWatch, and CloudTrail
• Strong Technical Experience (3+ to 6+ years) with Snowflake Data Cloud: Account administration, optimal virtual warehouse clustering strategies, and budget-optimization
• Strong Technical Experience (3+ to 6+ years) with Snowflake Data Cloud: Expert feature implementation: Data Sharing, Time Travel, and Zero-copy cloning
• Strong Technical Experience (3+ to 6+ years) with dbt (Data Build Tool): Managing multi-repository dbt projects and configuring dbt Cloud environments
• Strong Technical Experience (3+ to 6+ years) with dbt (Data Build Tool): Creating, documenting, and optimizing advanced dbt models and custom macros
• Strong Technical Experience (3+ to 6+ years) with AI-Assisted Engineering & Data Tools: Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, or Claude/OpenAI APIs) to maximize development efficiency
• Strong Technical Experience (3+ to 6+ years) with AI-Assisted Engineering & Data Tools: Familiarity with cloud-native AI services (e.g., Snowflake Cortex or AWS Bedrock) for embedding LLM capabilities directly inside the data layer
• Strong Technical Experience (3+ to 6+ years) with AI-Assisted Engineering & Data Tools: Exposure to frameworks used for AI data preparation (e.g., LangChain, Vector Databases, or text embedding generation)
• Strong Technical Experience (3+ to 6+ years) with Data Ingestion & Integration: Incremental loading and Change Data Capture (CDC) methods
• Strong Technical Experience (3+ to 6+ years) with Data Ingestion & Integration: Extensive experience querying and integrating with complex external REST APIs
• Strong Technical Experience (3+ to 6+ years) with Version Control & CI/CD: Advanced Git/GitHub branching strategies, pull request enforcement, and automated deployment pipelines
• Familiarity (1+ years of experience) with Orchestration & Scheduling: Tools like Prefect, Airflow, or similar modern workflow management software
• Familiarity (1+ years of experience) with Data Replication: Enterprise tools such as Qlik Replicate
• Soft Skills & Collaboration: A 'Product-First' Mindset: Demonstrated ability to partner directly with business users and stakeholders to gather solution requirements and translate them into technical assets
• Soft Skills & Collaboration: Collaborative Drive: Ability to work productively across parallel tracks (Software, Devops, Data) to achieve corporate objectives while protecting engineering quality
• Soft Skills & Collaboration: Technical Curiosity: A sharp mind and willingness to quickly master new technologies, architectures, and changing business domains
• Physical & Office/Site Presence Requirements: This is primarily a sedentary office position which requires the incumbent to have the ability to operate computer equipment, speak, hear, bend, stoop, reach, lift, and move and carry up to 25 lbs
• Physical & Office/Site Presence Requirements: Travel up to 10% of the time to Divisions within the Lennar family
• Physical & Office/Site Presence Requirements: Interact well with co-workers
• Physical & Office/Site Presence Requirements: Cross train for position(s) within the team organizational structure from time to time, as required by the Leadership Team
• Physical & Office/Site Presence Requirements: Comply with and implement company policies and procedures
• Physical & Office/Site Presence Requirements: Accept constructive criticism
• Physical & Office/Site Presence Requirements: Strong work ethic
• Physical & Office/Site Presence Requirements: Team player
• AWS Certification is a strong plus