Job description

Lead Data Engineer We are Lennar 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 by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States. A Career that Empowers You to Build Your Future The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. The Lead Data Engineer will provide technical leadership to our Product Team. This is done by helping design and implement our next generation data and analytics platforms and products using Data engineering best practices. The Lead Data Engineer also will implementing engineering solutions along with the team. In addition, this person focuses on empowering and enabling our business users through self-service and automation. The Lead Data Engineer is a key role in operationalizing Lennar’s enterprise data fabric. Your Responsibilities on the Team Design, Build, and Operationalize: Formulate production-grade data engineering solutions for Lennar’s data and analytics platforms and products. Pipeline Architecture: Architect and implement reliable ETL, ELT, and streaming data ingestion/delivery processes across multiple enterprise sources. Modern Python Development: Develop, maintain, and containerize modular data applications and utility scripts using Python, leveraging modern cloud infrastructure. Scale and Improve Infrastructure: Improve data ingestion architecture, emphasizing data quality, cost-performance, maintainability, and extensibility across storage and compute layers. Enforce Standards and Downstream Integrity: 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. Platform Observability: Instrument data analytics platforms with robust metrics, alerting, and automated monitoring (SLAs/SLOs) to ensure high availability and data trustworthiness. AI-Driven Productivity: Leverage modern AI-assisted development tools within daily engineering workflows to accelerate code generation, optimize heavy queries, and improve overall delivery speed. AI/ML Integration: Collaborate with data science teams to design and optimize data layers specifically tailored for Generative AI applications, Retrieval-Augmented Generation (RAG), and LLM frameworks. Ecosystem Integration: Wrangle and integrate data from highly disparate production systems to allow data analysts and data scientists to leverage optimized, end-to-end data products. Business Alignment: 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). Advanced Data Transformations: Designing complex operational pipelines, data cleanup, and robust standardization strategies. Production SDLC & Workflow Best Practices: Rigorous code reviews, end-to-end testing/QA methodologies, and resilient error-handling frameworks. 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. AWS Platform & Containerization: Hands-on experience deploying, managing, and scaling containerized data workloads using AWS ECS (Elastic Container Service) and ECR. Core AWS architecture: S3, IAM, Lambda, EC2, CloudWatch, and CloudTrail. AWS Certification is a strong plus. Snowflake Data Cloud: Account administration, optimal virtual warehouse clustering strategies, and budget-optimization. Expert feature implementation: Data Sharing, Time Travel, and Zero-copy cloning. dbt (Data Build Tool): Managing multi-repository dbt projects and configuring dbt Cloud environments. Creating, documenting, and optimizing advanced dbt models and custom macros. AI-Assisted Engineering & Data Tools: Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, or Claude/OpenAI APIs) to maximize development efficiency. Familiarity with cloud-native AI services (e.g., Snowflake Cortex or AWS Bedrock) for embedding LLM capabilities directly inside the data layer. Exposure to frameworks used for AI data preparation (e.g., LangChain, Vector Databases, or text embedding generation). Data Ingestion & Integration: Incremental loading and Change Data Capture (CDC) methods. Extensive experience querying and integrating with complex external REST APIs. 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. 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. Collaborative Drive: Ability to work productively across parallel tracks (Software, Devops, Data) to achieve corporate objectives while protecting engineering quality. 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. Finger dexterity is necessary. 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. This description outlines the basic responsibilities and requirements for the position noted. This is not a comprehensive listing of all job duties of the Associates. Duties, responsibilities and activities may change at any time with or without notice. #LI-KB2 This information is intended to be a general overview and may be modified by the company due to factors affecting the business. General Overview of Compensation & Benefits: We reasonably expect the base compensation offered for this position to range from an annual salary of $121,700.00 - $152,100, subject to adjustment based on business-related factors such as employee qualifications, geographic pay differentials (e.g., cost of labor/living, etc.), and operational considerations. This position may be eligible for bonuses. This position may be eligible for commissions. This position will be eligible for the described benefits listed in the above section in accordance with Company Policy. This information is intended to be a general overview and may be modified by the Company due to factors affecting the business. Life at Lennar At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life s critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone’s Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar’s policies and applicable plan terms. Visit Lennartotalrewards.com to view our suite of benefits. Join the fun and follow us on social media to see what s happening at our company, and don t forget to connect with us on Lennar: Overview | LinkedIn for the latest job opportunities. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.

Requirements

Must-haves

Lead Data Engineer
We are Lennar
A Career that Empowers You to Build Your Future
The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization.
Your Responsibilities on the Team
Design, Build, and Operationalize: Formulate production-grade data engineering solutions for Lennar’s data and analytics platforms and products.
Pipeline Architecture: Architect and implement reliable ETL, ELT, and streaming data ingestion/delivery processes across multiple enterprise sources.
Modern Python Development: Develop, maintain, and containerize modular data applications and utility scripts using Python, leveraging modern cloud infrastructure.
Scale and Improve Infrastructure: Improve data ingestion architecture, emphasizing data quality, cost-performance, maintainability, and extensibility across storage and compute layers.
Platform Observability: Instrument data analytics platforms with robust metrics, alerting, and automated monitoring (SLAs/SLOs) to ensure high availability and data trustworthiness.
AI-Driven Productivity: Leverage modern AI-assisted development tools within daily engineering workflows to accelerate code generation, optimize heavy queries, and improve overall delivery speed.
AI/ML Integration: Collaborate with data science teams to design and optimize data layers specifically tailored for Generative AI applications, Retrieval-Augmented Generation (RAG), and LLM frameworks.
Ecosystem Integration: Wrangle and integrate data from highly disparate production systems to allow data analysts and data scientists to leverage optimized, end-to-end data products.
Business Alignment: Gain a deep understanding of core business processes and align technical data development with strategic business objectives.
Data Architecture & Enterprise Modeling: Advanced data warehousing concepts, cloud data lakes, and structured multi-layer designs (Bronze, Silver, Gold).
Advanced Data Transformations: Designing complex operational pipelines, data cleanup, and robust standardization strategies.
Production SDLC & Workflow Best Practices: Rigorous code reviews, end-to-end testing/QA methodologies, and resilient error-handling frameworks.
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.
Hands-on experience deploying, managing, and scaling containerized data workloads using AWS ECS (Elastic Container Service) and ECR.
Core AWS architecture: S3, IAM, Lambda, EC2, CloudWatch, and CloudTrail.
AWS Certification is a strong plus.
Account administration, optimal virtual warehouse clustering strategies, and budget-optimization.

Nice-to-haves

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Keywords to mirror

pythonci/cdaimlllmapiawsrest

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Parental Leave