Data Engineer

Company Description Impact Bridge Consulting partners with growth-stage teams to install a hire-to-performance system that enables sustainable, scalable results. Using The Bridge Method™ (Fit • Grow • Impact), the firm helps organizations define success upfront, reduce mis-hires, and build leaders who execute reliably. By connecting role clarity, structured selection, and thoughtful onboarding and integration, Impact Bridge ensures teams ramp quickly and maintain performance beyond the first few months. The company also supports clients in establishing strong operating cadences so that performance and accountability are embedded into everyday work. This approach attracts professionals who value measurable impact, clear expectations, and leadership development.Role Description This is a full-time Data Engineer role based in the Dallas–Fort Worth Metroplex, structured as a hybrid position with a blend of on-site collaboration and work-from-home flexibility. The Data Engineer will design, build, and maintain scalable data pipelines that support client-facing analytics, internal reporting, and performance insights. Day-to-day responsibilities include implementing and optimizing ETL processes, integrating data from multiple sources, and ensuring data quality, reliability, and security across environments. The role will involve modeling and organizing data in warehouses and related structures to support reporting, dashboards, and advanced analytics for both Impact Bridge and its clients. The Data Engineer will collaborate closely with consultants, product, and operations teams to translate business requirements into robust data solutions and to improve data infrastructure over time.QualificationsStrong data engineering skills, including experience designing and maintaining data pipelines and working with modern data engineering tools and platforms.Proficiency in data modeling and data warehousing to support reporting, analytics, and scalable storage structures.Hands-on experience with Extract Transform Load (ETL) processes, including building, scheduling, and optimizing ETL workflows.Ability to support data analytics efforts, including preparing data for dashboards, reports, and performance metrics.Proficiency in SQL and at least one programming language commonly used in data engineering (such as Python or Scala).Familiarity with cloud data platforms (e.g., AWS, Azure, or GCP) and related data services is strongly preferred.Experience with version control, testing, and documentation practices in a data engineering context.Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.Ability to work effectively in a hybrid environment, communicate clearly with non-technical stakeholders, and manage multiple priorities.Interest in performance, leadership development, and using data to drive measurable impact for teams and organizations.