Data Engineer Jobs in Irving, TX

Design, build, and maintain optimized, highly available data pipelines and the BMG data warehouse. Lead medium-to-complex data engineering initiatives, perform solution design, code reviews, QA, data integration, and collaborate across teams. Support cloud migration and ensure compliance with data policies for reporting and analytics.

Design, architect, and deliver scalable data pipelines and storage solutions using big data and cloud technologies. Lead technical strategy, mentor engineers, ensure data governance, security, and performance, and collaborate with Data Science and Product teams to support analytics and ML initiatives.

Design, build, test, deploy, and monitor batch and streaming data pipelines and ETL processes. Evaluate and adopt data technologies (including Adobe Experience Platform and CDPs), collaborate with data scientists, architects, and business partners to ingest and prepare large semi-structured/unstructured datasets for ML training, model execution, and search analytics, and implement automation, documentation, and tooling for scalable analytic data systems.

As a Sr Data Engineer, you'll conduct feasibility analyses, develop applications, monitor processes, consult with users, and ensure compliance while serving as a mentor to junior analysts.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Develop and optimize scalable data solutions within the Hadoop ecosystem, implement real-time data streaming, and mentor team members while focusing on AI and machine learning integration.

Design, build, and operate cloud-native, domain-oriented data products and pipelines across Azure and AWS using Databricks and Snowflake. Lead migration from legacy platforms, implement batch and streaming processing with Spark, ensure security and governance compliance, promote best practices (CI/CD, testing, observability), and mentor junior engineers while collaborating with product, analytics, and security teams.

Design, build, and support an AI-ready enterprise data enablement platform using Databricks, dbt, Delta Lake, and Azure data services. Create reusable CI/CD and IaC accelerators, govern data products via Unity Catalog, enable analytical access with Starburst/Trino, troubleshoot production issues, and collaborate with cross-functional teams to deliver governed, reusable, and production-grade data products for analytics and GenAI use cases.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate with Airflow, ingest from 3rd-party APIs, optimize columnar formats and SQL, support ML workflows, consult stakeholders, and provision AWS/on-prem infrastructure with Terraform.

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.

Design, develop, maintain, and optimize enterprise Tableau dashboards and BI solutions. Integrate and cleanse data from Oracle/Sybase/Big Data, tune SQL, automate Tableau extracts, manage Tableau Server on Linux, support testing, UAT, deployments, and troubleshoot data integrity and performance issues.

The Senior Data Engineer will design, build, and maintain scalable data solutions, conducting feasibility studies, managing the development process, and ensuring high-quality code and compliance with industry standards.

The Data Solutions Engineer develops Big Data solutions, migrating workloads to cloud platforms and collaborating with stakeholders for optimal data implementations.

Provide technical and business support for Citi applications, manage application environments, perform risk analysis, and lead enhancements while ensuring compliance with corporate standards.

The role requires designing, building, and maintaining data pipelines using Big Data technologies. Responsibilities include developing ETL processes, ensuring data integrity, collaborating with teams, and applying AI techniques to drive efficiency.

The Data Engineer will design and maintain data pipelines using Big Data technologies, optimize ETL processes, and apply AI techniques. Responsibilities include collaborating on data solutions and ensuring data quality and security.

Lead design and implementation of large-scale data pipelines, ETL, and warehousing. Build and manage databases, ensure data quality/security, collaborate with analysts and scientists, evaluate new technologies, mentor junior engineers, and manage project delivery.

Lead hands-on data engineering and applied ML work: build, train, evaluate, and productionize models and data products; surface insights, detect anomalies, and translate findings into business value across products, transactions, and customer behavior while partnering with cross-functional stakeholders.

Lead and architect high-performance SQL Server VLDB solutions (SQL Server 2019+). Own performance tuning, ETL/data loading (SSIS/SSAS), data modeling, security (TDE/entitlements), code reviews, AI-assisted optimization, mentor teams, and manage delivery of scalable data warehouse pipelines.

Design, build, and support full-stack web applications and microservices to provide self-service test data capabilities. Develop Java/Spring Boot backend services and React front-ends, design RESTful APIs, automate test data provisioning, contribute to CI/CD pipelines, and provide production support and engineering best practices across teams.

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.

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.

Lead design, maintenance, and optimization of on-prem and cloud data platforms. Perform DBA duties for SQL Server, manage HA/DR and replication, troubleshoot performance, lead on-prem to Azure migrations, maintain Azure data services and Microsoft Fabric, optimize cloud cost/performance, implement monitoring, collaborate with architects and BI teams, and mentor junior engineers.

Provide production application and Big Data platform support for critical financial systems: monitor, troubleshoot, tune Hadoop/Cloudera clusters, manage incidents and releases, maintain runbooks, perform risk reconciliations, liaise with stakeholders and vendors, drive stability and SRE best practices, and coach junior staff.

Lead SRE and production support for big data services: manage incident/problem management, monitoring/observability (AppDynamics, Splunk, ELK, Grafana), service improvement, automation (Ansible, CI/CD), disaster recovery, capacity/configuration/change management, and coordinate with development, architecture, and infrastructure teams while leading L2 service delivery and on-call support.