Lead Data Engineer at Banner Health in Phoenix, AZ

Lead Data Engineer Location: Banner Health Corp Phoenix (2901 N Central Ave) Primary City/State: Phoenix, Arizona Department Name: Digital Transform-Foundation Work Shift: Day Job Category: Information Technology Estimated Pay Range: $53.63 - $89.38 / hour Banner Health is committed to pay equity and transparency. The posted compensation range is a reasonable estimate that extends from the lowest to the highest pay Banner Health in good faith believes it might pay for this particular job, based on the circumstances at the time of posting. This range is based on possible base salaries and does not include the value of our total rewards package. Actual pay determined at offer will be based on years of relevant work experience, education, certifications, skills, and geographic location, along with a review of current employees in similar roles to ensure pay equity is achieved and maintained. Within Banner Health Corporate, you will have the opportunity to apply your unique experience and expertise in support of a nationally-recognized healthcare leader. We offer stimulating and rewarding careers in a wide array of disciplines. Whether your background is in Human Resources, Finance, Information Technology, Legal, Managed Care Programs or Public Relations, you'll find many options for contributing to our award-winning patient care. POSITION SUMMARY This position helps to design, build, and scale Banner Health’s next-generation data platform on the cloud. This role leads the engineering of reliable, secure, and scalable data products and pipelines that power analytics, reporting, AI, and operational insights across clinical and business domains. Works closely with architects, analysts, data scientists, product teams, and business leaders to modernize how data is ingested, governed, transformed, and consumed across the organization. CORE FUNCTIONS 1. Designs, builds, and optimizes scalable batch and streaming data pipelines for enterprise analytics and operational use cases. Contributes to the evolution of the enterprise data platform to support advanced analytics, self-service consumption, and AI/ML use cases. 2. Leads the development of curated, high-quality data products across lakehouse, warehouse, and domain-oriented data architectures. 3. Builds and enhances cloud-native data solutions using modern platforms such as Databricks, Spark, Delta Lake, and AWS services. 4. Establishes and enforces engineering standards for code quality, testing, CI/CD, observability, lineage, and documentation. 5. Drives best practices for data quality, schema evolution, performance tuning, reliability, and cost optimization. 6. Partners with architecture, governance, security, and analytics teams to implement trusted and compliant data solutions. 7. Supports ingestion and transformation of complex healthcare and enterprise data sources, including structured, semi-structured, and high-volume event data. 8. Mentors engineers, provides technical leadership, and contributes to solution design, estimation, and delivery planning. 9. Translates business and operational requirements into scalable technical designs and production-ready data pipelines. MINIMUM QUALIFICATIONS Must possess strong knowledge of data engineering and analytics as normally obtained through the completion of a Bachelor's degree in Data Science, Computer Science, Information Technology or a related field. Must have 6+ years of experience in data engineering, big data, analytics engineering, or data platform development. Must have 3+ years in a senior or lead engineering role driving architecture, standards, and delivery across large-scale data environments. Must have strong hands-on experience with Databricks, Apache Spark, Delta Lake, and cloud-based data platforms on AWS, Azure, or GCP. Deep expertise in SQL and strong programming skills in Python and/or Java0 Experience building and operating large-scale distributed data systems, including data lakes, lakehouses, warehouses, or mesh-oriented platforms. Must have a strong understanding of data modeling, partitioning, storage design, metadata management, and performance optimization. Experience implementing data quality, lineage, observability, and operational monitoring in production environments. Familiarity with orchestration, DevOps, and CI/CD practices for data platforms. Must have strong communication skills and the ability to work effectively with technical and non-technical stakeholders. Proven ability to balance multiple priorities in a fast-paced environment while maintaining high engineering standards. PREFERRED QUALIFICATIONS Experience in healthcare, payer-provider, clinical, or regulated data environments. Familiarity with EHR, claims, FHIR, HL7, interoperability, or other healthcare data standards. Experience with governance and secure access models using tools such as Unity Catalog, Lake Formation, or equivalent. Experience supporting AI/ML, feature engineering, vector or unstructured data pipelines, or data products for GenAI use cases. Exposure to infrastructure-as-code, automated testing, and platform engineering practices. Experience mentoring engineers and influencing cross-functional technical direction. Additional related education and/or experience preferred. Anticipated Closing Window (actual close date may be sooner): 2026-09-02 EEO Statement: EEO/Disabled/Veterans Our organization supports a drug-free work environment. 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