Top Data Engineer Jobs in Dallas, TX

Design, build, test, and maintain secure, scalable data pipelines and architectures. Work with Python, Databricks, SQL/NoSQL, and enterprise AI capabilities to deliver trusted data collection, storage, access, and analytics. Validate AI-assisted outputs, update data models, customize tools, and ensure controls, traceability, and data sensitivity handling.

Design, implement, and manage advanced data ecosystems and scalable ETL/ELT pipelines. Analyze complex problems, deliver data warehousing and governance solutions, mentor junior staff, and build client relationships while maintaining high standards and business-context awareness.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead and manage delivery of modern data ecosystems and managed data analytics programs. Oversee project planning, budgeting, quality, and client accounts. Mentor teams, drive data strategy, convert insights to business opportunities, and ensure standards and risk management across large transformations.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Develop and maintain data pipelines and ETL processes, optimize SQL and data architectures, build BI reports and dashboards (Oracle BI, QlikView, Spotfire), analyze data to produce strategic insights, support client engagements in regulated environments, and apply continuous process improvements to ensure data quality and integrity.

Lead design, develop, test, and support cloud-based data platforms and scalable data pipelines. Mentor engineers, collaborate with product managers, and deliver high-performance data lakehouse/warehousing and event-driven solutions using big data and cloud technologies.

Lead design and build scalable, low-latency, fault-tolerant streaming data platforms and distributed data pipelines. Own streaming analytics, cloud-based data stores, CI/CD practices, and mentor engineers while collaborating with product, security, and ML teams to deliver robust cloud solutions.

Lead design, build, and support of Azure-based data pipelines and solutions. Develop ETL using Azure Data Factory, optimize Azure SQL/SQL Server, implement CI/CD for data workloads, perform data modeling, ensure data quality and governance, and provide production support in an Agile team.

Design, build, and optimize HANA-native data models and analytical objects for S/4HANA, BW/4HANA, and standalone HANA. Translate business requirements into performant calculation views, CDS views, AMDPs and SQLScript. Diagnose and resolve HANA performance issues, use replication tools (SLT/SDI/SDA), enforce HANA security, and support migrations, tuning, and documentation.

Lead design and build scalable, low-latency, fault-tolerant data platforms and pipelines. Mentor engineers, influence data architecture and governance, build analytics stores using big-data and cloud technologies, collaborate with product and security teams, and ensure CI/CD, resiliency, testing, and performance for data-driven solutions.

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.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

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.

As a Lead Data Engineer, you will design and develop solutions, collaborate with teams on data technologies, and support cloud-based data warehousing and big data applications.

Contribute to building and maintaining cloud-based data pipelines and data products. Develop, test, and optimize SQL and Python transformations, participate in code reviews, troubleshoot data quality issues, and follow CI/CD and documentation practices to support analytics and AI initiatives.

Join the BI and Data Engineering team to design and implement data solutions, develop ETL processes, create solution architecture and technical design artifacts, collaborate with onshore/offshore teams, lead technical meetings, and present solutions to stakeholders.

Lead design and build scalable data processing and control-plane solutions on Databricks/AWS. Develop Python/PySpark/SQL pipelines, APIs/SDKs, governance, observability, CI/CD, and operational runbooks. Mentor engineers, drive adoption of AI-assisted development, and ensure data quality, security, lineage, and platform reliability.

As a Data Engineer, you'll deliver scalable data solutions, participate in technical discussions, and ensure timely, trustworthy data delivery through robust pipelines.

Build and maintain scalable data pipelines, implement ingestion/transformation and data quality, design data models and export solutions, support production jobs, write tests, evaluate technologies, and collaborate with stakeholders to deliver analytics-ready data.

Design, build, and maintain scalable cloud data pipelines and platform components to power analytics, ML, and applications. Implement transformations, data quality checks, lineage and governance, optimize performance and cost, monitor platform health, and build reusable components across business units while collaborating with product and architecture teams.

Lead design, build, and operate reusable, secure, cloud-native data platforms on Google Cloud. Create ingestion, transformation, orchestration frameworks, enforce governance, optimize cost/performance, enable self-service analytics and AI, and provide enablement and runbooks for product and domain teams.