Data Engineer

Data Analytics Engineer Location: Irving, Texas, United States (Hybrid) Industry: Hospitals and Health Care Work Setting: Hybrid Are you passionate about transforming complex data into trusted, scalable analytics solutions? We're looking for a Data Analytics Engineer to design, build, and optimize enterprise data solutions that drive business insights and operational excellence.

In this role, you'll focus on improving data quality, modernizing existing data platforms, developing reusable data assets, and enabling efficient reporting and analytics through robust engineering practices.

What You'll Do

• Design and implement scalable data quality frameworks to validate data completeness, accuracy, consistency, timeliness, and adherence to business requirements.
• Identify and remediate technical debt by standardizing development practices, simplifying data workflows, and improving overall system reliability and maintainability.
• Develop and manage data retention and archival strategies, including governed lifecycle and purge processes that support compliance and operational needs.
• Build and maintain consolidated, reusable datasets that serve as trusted sources for analytics, reporting, and business decision-making.
• Design and support dimensional data models, including star-schema architectures, to enhance reporting performance and ensure consistent metric definitions.
• Develop, optimize, and maintain data pipelines using modern cloud-based data platforms, APIs, and scalable engineering frameworks.
• Create and maintain technical documentation, data lineage records, validation rules, operational procedures, and support materials to ensure long-term sustainability.
• Collaborate closely with engineers, analysts, and business stakeholders to gather requirements, align on data definitions, communicate risks, and deliver high-impact solutions.

Required Qualifications

• Bachelor's degree or equivalent practical experience in a relevant field.
• 4+ years of experience in data engineering, analytics engineering, software development, or related disciplines.
• Strong experience building and supporting production-grade data platforms and pipelines.
• 4+ years of hands-on experience with modern data warehouse or lakehouse technologies.
• Proficiency in Python and SQL for data engineering, automation, validation, and analytics solutions.
• Experience implementing data quality controls, monitoring frameworks, and issue remediation processes.
• Solid understanding of dimensional modeling, data warehousing concepts, database design, and enterprise data architecture.
• Ability to translate business requirements into scalable technical solutions and effectively communicate with both technical and non-technical audiences.
• Knowledge of data governance, security, lineage, retention policies, and production support best practices.

Preferred Qualifications

• Experience working with large-scale and complex datasets.
• Familiarity with Agile project management tools and delivery methodologies.
• Knowledge of cloud-based data and analytics platforms.
• Experience with business intelligence and data visualization tools for reporting and dashboard development.