Data Engineer Jobs in Irving, TX

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 scalable cloud-native data pipelines, microservices, and platforms to support real-time and batch processing. Collaborate with architects and stakeholders to translate requirements, implement AWS-based ingestion/streaming solutions, enforce data quality/testing, and operate observability and CI/CD practices to ensure reliable production data systems for autonomy initiatives.

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.

Design, build, and maintain enterprise analytics solutions and semantic data models using Microsoft Fabric, Databricks, SQL, Python, and BI tools. Deliver scalable reporting datasets, executive dashboards, data quality standards, and CI/CD practices. Lead architecture discussions, mentor engineers, collaborate with stakeholders, and drive analytics strategy to enable data-driven decisions.

Lead design, build, and operate scalable data pipelines, microservices, and cloud-native data platforms. Collaborate with architects and stakeholders to translate requirements, ensure data quality and testing, implement streaming and batch solutions on AWS, and maintain operational excellence, monitoring, and CI/CD for high-availability data systems supporting autonomy initiatives.

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.

Builds and operates scalable batch and real-time data pipelines (Databricks/Spark, Kafka), maintains Customer 360 data model and feature pipelines, ensures data quality/governance, delivers governed customer attributes to activation platforms, and supports privacy/compliance.

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.

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.

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.

Design and build high-scale data systems, predictive models, and interactive dashboards to drive consumer sales, planning, and marketing. Lead data modeling (LookML), ETL development, BigQuery/Vertex AI implementation, data quality initiatives, and mentor peers while translating analytics for non-technical stakeholders.

Design, build, and maintain ETL/ELT pipelines and API integrations to ingest, cleanse, transform, and analyze infrastructure and cloud data. Produce analytics, dashboards, and executive reports; automate workflows and support near-real-time processing. Follow SDLC/DevOps practices (Git, CI/CD), ensure data governance, quality, lineage, and support incident, release, and compliance activities.

Design and develop end-to-end data engineering solutions for digital and marketing initiatives. Build data-driven applications using Python, Spark, and Hadoop; integrate data from Hadoop, Oracle, MSSQL and ELZ; optimize database performance; develop APIs and integration services; monitor systems with Splunk and Datadog; create technical and business specification documents; design and support Adobe Campaign messaging templates and campaigns; collaborate with architects and analysts to deliver scalable, reliable solutions.

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

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 and build of scalable Azure-based data pipelines, lakehouse architectures, and optimized data models. Implement CI/CD, data governance, real-time streaming, and productionize ML feature pipelines while mentoring engineers and collaborating with analysts and business stakeholders to enable analytics and regulatory-compliant data operations.

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.

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.

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.

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.