Sr Data Quality Engineer

Lennar•Waterford, FL

3d•Onsite

About The Position

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. Join a Company that Empowers you to Build your Future The primary mission of the Data Quality Engineer role is to help our business evolve into an AI-first, data-driven organization built on a foundation of trusted, governed, and reliable data. The position sits in our Data & AI team which aims to drive improved business outcomes using insights gleaned from data and analytics and infuse them into Lennar’s corporate fabric. The Data Quality Engineer will design, implement, and operationalize enterprise-grade data quality and master data management frameworks, ensuring the integrity, consistency, and accuracy of critical data across all platforms. This role will be instrumental in deploying and managing tools such as Ataccama and Reltio, building intelligent data quality pipelines, and leveraging AI-driven technologies including AWS Bedrock and Agentic AI to automate quality monitoring and remediation 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

5–7 years of experience in data quality engineering, data management, or a closely related data engineering discipline
Strong proficiency in SQL/Python for data analysis, quality rule development, and reconciliation across relational and cloud-native databases
Hands-on experience with Ataccama ONE or Ataccama DQ for data profiling, quality rule authoring, workflow management, and MDM integration
Demonstrated experience implementing and managing Master Data Management solutions, with specific expertise in Reltio preferred
Experience working in AWS cloud environments; familiarity with AWS services relevant to data quality and governance (S3, Glue, Lambda, Step Functions)
Proficiency with Snowflake, including data quality patterns, dynamic data masking, and leveraging Snowflake’s native data quality features
Familiarity with AWS Bedrock, Claude Code, Codex and experience applying generative AI or Agentic AI frameworks to automate or augment data operations workflows
Solid understanding of data governance principles, data cataloging, metadata management, and data lineage concepts
Experience with data quality metrics definition, SLA management, and executive-level reporting on data health
Ability to work collaboratively with business users, data stewards, and technical teams to gather requirements and deliver data quality solutions
Strong adherence to software engineering best practices including version control (git), modular code design, Agile methodologies, and CI/CD pipelines
Ability and willingness to quickly learn emerging data quality technologies and adapt to an evolving enterprise data landscape
Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field; equivalent practical experience will be considered

Responsibilities

Design and implement end-to-end data quality frameworks, including profiling, cleansing, validation, and monitoring across enterprise data assets
Deploy and administer Ataccama DQ and MDM capabilities to enforce data quality rules, lineage tracking, and issue resolution workflows
Configure and manage Master Data Management (MDM) solutions using Reltio to create and maintain golden records for critical business entities such as customers, products, and vendors
Build and maintain data quality pipelines in Snowflake and AWS cloud environments, leveraging native features for scalable quality checks and anomaly detection
Develop and maintain SQL-based data quality rules, reconciliation queries, and automated validation scripts across structured and semi-structured data sources
Integrate AI and machine learning capabilities via AWS Bedrock and Agentic AI frameworks to enable intelligent, self-healing data quality processes and automated root cause analysis
Define and track data quality KPIs and SLAs; produce dashboards and reports to communicate quality health to business and technology stakeholders
Partner with data governance, data engineering, and business teams to establish enterprise data standards, taxonomies, and ontologies
Lead data quality issue triage, root cause analysis, and remediation efforts in collaboration with upstream data owners and platform teams
Support CI/CD practices for data quality rule deployment, version control, and automated regression testing
Contribute to the development of data qualities policies, standards, and best practices documentation
Champion a culture of data trust across the organization through training, evangelism, and hands-on enablement of data consumers and producers