Analytics Engineer III job at Children's Medical Center in Dallas, TX

Analytics Engineer III

Location: Dallas, TX, United States

Job Id 31424

Job Description:

Job Title & Specialty Area: Analytics Engineer III (Microsoft Fabric, Power BI)

Department: Enterprise Data and Analytics

Location: Dallas, TX

Shift: 8:00 am to 5:00 pm

Job Type: Remote

Why Children's Health?

At Children's Health, our mission is to Make Life Better for Children, and we recognize that their health plays a crucial role in achieving this goal.

Through our cutting-edge treatments and affiliation with UT Southwestern, we strive to deliver an extraordinary patient and family experience, ensuring that every moment, big or small, contributes to their overall well-being.

Our dedication to promoting children's health extends beyond our organization and encompasses the broader community. Together, we can make a significant difference in the lives of children and contribute to a brighter and healthier future for all.

Summary:

Under minimal direction of data & analytics engineering leadership, the Analytics Engineer III will lead analytics engineering at scale for complex healthcare domains (e.g., enterprise surgical analytics, clinical outcomes, enterprise supply chain analytics), design semantic and product solution architectures (metrics stores, knowledge graphs), embed governance controls, shape analytics federated delivery, and mentor teams to raise analytics engineering maturity. This role will be working closely with operational stakeholders, product team members, and data stewards to ensure successful delivery of analytics products that support business goals. Analytics engineers bridge data engineering and analytics development to deliver analytics-ready data assets, semantic layers, metric stores, analytics models/marts, and operationalized anlaytics products for clinical and operational domains at Children's Health. This role family supports domain-aligned analytics, federated CI/CD and lifecycle management for analytics artifacts, and close collaboration with clinical, financial, supplychain and operational stakeholders.

Responsibilities:

Core Responsibilities:

Prepare and model analytically ready datasets; implement and maintain semantic layers, metrics stores or data marts; apply data engineering best practices to analytics (version control, CI/CD, environment management); collaborate with BI analysts, data scientists and domain stakeholders to operationalize analytics products; ensure alignment with governance and data quality requirements

Level Specific Requirements:

Architect and govern domain semantic layers, metrics stores and knowledge-graph integrations that combine structured and unstructured clinical, operational and supplychain data to enable conversational analytics and agent-driven workflows

Drive analytics engineering best practices enterprise-wide: code/version control, CI/CD, testing, performance engineering, metadata governance and observability to ensure high model/analytics uptime and low defect rates

Ensure analytics products meet regulatory, privacy and security requirements for healthcare data; partner with governance, ARB and security teams for AI/analytics artifacts that impact clinical workflows

Lead cross-functional delivery for high-impact use cases (procedural analytics driving clinician behavior, demand planning integrated with scheduling/EHR, control tower for inventory and disruption management)

Mentor and upskill analytics engineers and BI teams; define role progression, create repeatable delivery patterns and measure analytics engineering maturity and business impact

Strategic domain ownership, stakeholder influence, ability to articulate ROI and value, mentor/lead technical teams and represent analytics engineering in architecture/governance forums

Shapes analytics engineering strategy and delivers high-impact analytics initiatives with minimal supervision

Technical and project oversight and mentorship to junior engineers and product analysts

Healthcare domain considerations:

Work with EHR/clinical data and supply‑chain/ERP data sources, follow interoperability expectations (FHIR/HL7 awareness for clinical integrations), support clinical analytics use cases (procedural analytics, outcomes measurement, preference card analytics) and supply‑chain analytics (spend, contract, inventory visibility) when relevant

Engineering practices to measure and apply:

Version control of analytics content, separate dev/test/prod environments, workflow orchestration, metadata/cataloging and performance testing to improve model uptime, adoption, code quality and defect resolution

Governance & risk:

Adhere to organizational data governance, privacy and security requirements (e.g., HIPAA-relevant controls), and collaborate with governance or ARB where analytics/AI artifacts will be used in clinical or high-risk contexts

How You’ll Be Successful:

WORK EXPERIENCE

At least 6 years Across data engineering, analytics engineering or analytics platform roles with proven exp