Top Data Engineer Jobs in Dallas, TX

As a Quality Engineer, you'll assist in monitoring product and process quality, investigate quality issues, and coordinate improvement initiatives using data analysis. You will measure performance through KPIs, maintain dashboards, analyze trends, and ensure data integrity in a cross-functional environment.

The Lead Data Engineer will manage and mentor a data engineering team to deliver data solutions for clients. Responsibilities include overseeing data pipeline development, ensuring client integrations, applying data best practices, and managing project timelines while contributing hands-on to technical decision-making and code reviews.

The Senior Data Engineer at Varsity Brands will design, build, and manage data pipelines, working with stakeholders to identify data sourcing needs and provide scalable data solutions while ensuring efficient pipelines and troubleshooting issues as they arise.

The Data Engineer II will design, develop, and support data integration and ETL projects, mentor other data engineers, and ensure the quality of BI data. Responsibilities include data profiling, logical/physical modeling, performance tuning, and collaborating with offshore teams on development tasks.

The Lead Data Engineer will create and maintain data pipelines, handle complex data transformations, and collaborate with development teams. Responsibilities include optimizing queries, automating processes, and improving data systems. The role requires troubleshooting and incident resolution while providing leadership to the team.

The Principal Analytics Engineer at Americor will bridge data engineering, data science, and business intelligence, driving analytics innovations. Responsibilities include building and deploying automated machine learning models, conducting audits for best practices, and delivering impactful analytics solutions through advanced reporting and statistical experimentation.

The Data Architect will support and enhance Data & Analytics platforms, focusing on data movement and database technologies for analytics and ML/AI. Responsibilities include identifying performance bottlenecks, leading architectural development, designing end-to-end solutions, collaborating with various teams, and ensuring project alignment with best practices.