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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Engineer - **Company:** Lennar Corporation - **Location:** Irving, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Cloud Computing, Cloud Database, Code Review, Continuous Integration, Data Architecture, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Sharing, Data Warehousing, Database Development, Github, Python (Programming Language), Systems Development Life Cycle, Role-Based Access Control, DataOps, SQL Databases, Data Streaming, Strategies of Testing, Management of Software Versions, Enterprise Data Management, Data Ingestion, Snowflake, Electronic Medical Records, Modularization, Git Flow, Data Analytics, Qlikview, Data Delivery, Cloudwatch, Restful APIs, Software Version Control, Data Pipelines - **Published:** May 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=befd3749ba72fa37 ## About the Role Do you have experience in Version control?, Technical Requirements * Expertise (At least 8+, prefers 12+ years) in: * Data Architecture design * Data modeling & Data warehousing concepts * Data transformations and standardizations * ETL processes & strategies * Monitoring and error handling * SDLC & workflow best practices * Code Reviews * QA/Testing methodologies * Strong experience (At least 3+, prefers 6+ years) with the following technologies and platforms: * AWS platform: S3, EC2, EMR, EKS, Glue, Lambda, AppFlow, Cloudwatch etc. * AWS certification is big plus * Snowflake Data Cloud * Account Administration * Virtual warehouse strategies * Snowflake feature implementation: Data Sharing, Time Travel, and Zero-copy cloning * Role-based Access Control strategies * Dbt * Managing dbt cloud environment * Managing multi-repository dbt projects * Creating and managing dbt models * Creating and leveraging dbt macros * Version control & branching strategies (Github a plus) * Proficient in languages: SQL, Python * Data governance, security, and compliance concepts * Data Ingestion * Incremental and CDC ingestion methods * REST APIs * Familiarity (At least 1+ years of experience) with: * Orchestration & scheduling tools (Prefect, Airflow is a plus) * Qlik Replicate Other Requirements * Ability to work collaboratively and productively with other team members to achieve Lennar's objectives. * Thirst to help transform Lennar into an insights-driven organization. * Demonstrated some experience in all aspects of development including, but not limited to, gathering requirements, development of technical components related to process scope and supporting testing and post implementation support. * Ability to work and partner with users and stakeholders to gather solution requirements. * Experience working with business users to understand how to optimally deliver insights within their operational workflows & decision-making processes. * Ability and willingness to quickly learn new technologies. * 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. ## Description The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. This position sits in our Enterprise Data and Analytics team, which aims to drive improved business outcomes using insights gleaned from data and analytics, infusing them into Lennar's corporate fabric. The Lead Data Engineer will provide technical leadership to our data platform engineering 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. * 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. Your Responsibilities on the Team * Design, build, and operationalize data engineering solutions for Lennar's data and analytics platforms and products. * Architect and implement ETL, ELT and streaming data ingestion data delivery processes across multiple sources. * Experience in data modeling, cloud data lake, cloud data warehouse * Instrument data analytics platforms with robust metrics and monitoring. * Improve data ingestion architecture, emphasizing data quality, maintainability, and extensibility. * Support process improvement on the team to enable rapid development of data products. * Define and Implement standards and best practices for data analytics team, including code modularization, versioning, testing, automation of CI/CD workflows, code reviews etc. * Gain an understanding of core business processes and align data development with business strategy. * Wrangle and integrate data from disparate systems to allow data analysts and data scientists to leverage end-to-end data and information. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What’s the Difference between a Junior, Mid, and Senior Developer?](https://www.wearedevelopers.com/magazine/238-what-s-the-difference-between-a-junior-mid-and-senior-developer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Why Attend a Developer Event in 2026?](https://www.wearedevelopers.com/magazine/688-why-attend-a-developer-event-in-2026) - [What Makes WeAreDevelopers World Congress Different From Every Other Tech Event?](https://www.wearedevelopers.com/magazine/701-what-makes-wearedevelopers-world-congress-different-from-every-other-tech-event)