Data Engineer Jobs in Irving, TX

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts; optimize Hadoop/HDFS workflows; integrate data science models; ensure data quality, accessibility, and production deployments; troubleshoot systems and recommend tooling improvements.

Design, build, and maintain large-scale data structures, ETL pipelines, data marts and models for analytics. Integrate data sources, ensure data quality, optimize Hadoop/Spark workflows, collaborate with Data Science to operationalize models, and recommend tooling and architecture improvements.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate and operationalize ML models, optimize Hadoop/HDFS workflows, ensure data quality, and collaborate with data science to support analytics and reporting needs.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Collaborate with Data Science to operationalize models, perform SQL/Python analysis, optimize BigQuery queries, ensure data quality, and support analytics and modernization initiatives across healthcare and retail domains.

Design, build, and maintain large-scale data structures, ETL pipelines, and data architectures. Integrate data sources, ensure data quality and accessibility, support data science and analytics, optimize Hadoop/HDFS workflows, and collaborate on backend services and ML infrastructure.

Build and manage large-scale data structures, pipelines, and ETL workflows; design databases and data marts; integrate data for analytics and Data Science; optimize Hadoop/Spark and cloud environments; collaborate with Data Science to operationalize models; test, troubleshoot, and recommend tooling. Hybrid role near Irving, TX.

Design, build, and maintain large-scale data structures and ETL pipelines using Hadoop/Hive, SQL, Python/Java. Support real-time and offline analytics, create data marts/models, integrate data sources, ensure data quality, collaborate with Data Science, and produce reporting/BI outputs.

Design, build, and maintain large-scale data structures, pipelines, and ETL workflows. Integrate data from varied sources, ensure data quality and privacy, collaborate with data science to operationalize models, optimize queries and Hadoop-based systems, and support analytics, reporting, and modernization initiatives.

Design, build, and manage large-scale data structures, ETL pipelines, and data marts to support analytics and data science. Integrate data from varied sources, ensure data quality and accessibility, optimize Hadoop/HDFS workflows, collaborate with data scientists to operationalize models, and recommend tooling and architectures to meet business needs.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models. Integrate data sources, ensure data quality and accessibility, support analytics and Data Science (including MLOps), optimize queries and distributed systems, and recommend tooling and architecture improvements for healthcare-related large-data environments.

Design, build, and maintain large-scale data structures, ETL pipelines, and data models. Integrate data sources, ensure data quality, support analytics and Data Science, optimize big data processing, and recommend tooling and solutions.

Design, build, and manage large-scale data structures, pipelines, and ETL workflows. Develop databases and real-time/offline analytic processing, support data science integration, optimize queries, build data marts and models, ensure data quality and privacy, and recommend tooling and architecture solutions.

Lead design and implementation of scalable data architectures and pipelines for real-time and batch processing; mentor junior engineers; ensure pipeline reliability, monitoring, security, and governance; collaborate with cross-functional teams and adopt new data technologies.

Lead the data engineering team to design, build, and scale data platforms and pipelines. Set standards, manage projects and technical debt, collaborate with stakeholders, drive adoption of new tools, ensure data governance, and provide technical leadership for complex data issues and real-time architectures.

The role involves design and development using Hadoop and its ecosystem, requiring strong programming skills in Java, Python, and SQL, with experience in data warehouses.

Design and build automated data validation and monitoring systems across clinical and AI pipelines. Translate business needs into validation frameworks, implement Python/C#/SQL checks, perform root-cause analysis, and embed data quality and compliance (HIPAA/SOC2) into data lifecycles. Collaborate with stakeholders to prioritize, deploy, and document automation and AI-assisted tooling.

The Lead Data Engineer at Lennar will design and implement data engineering solutions, lead the data platform team, and ensure data quality and accessibility for business insights.

The Senior Data Developer Tech Lead will design and manage scalable data solutions within Hadoop, lead streaming data architecture, optimize performance, and integrate AI/ML capabilities, while coaching team members and ensuring best practices in the banking domain.

Lead the design and implementation of Hadoop architecture and real-time data solutions. Coach team members, optimize performance, and ensure data governance within a small agile squad, focusing on AI/ML capabilities.

As a Software Engineer, you'll design AI applications, implement multi-agent architectures, build RAG pipelines, and ensure enterprise-grade reliability by optimizing performance and collaborating with teams.