Top Healthtech Data & Analytics Jobs

Own analytical direction for a business domain, establish and govern metric definitions, lead two to three data analysts, prioritize analysis, and resolve complex healthcare data questions. The role requires deep SQL, dbt modeling, data validation, cross-functional communication, and expertise in PHI and HIPAA requirements. Preferred experience includes pharmacy or payer data, Looker and LookML, Python, patient-support programs, and metric-layer ownership.

Designs and delivers predictive, prescriptive, and diagnostic analyses that guide strategic decisions. Owns the analytical lifecycle, including hypothesis development, statistical and machine learning modeling, experimentation, metric governance, data quality, documentation, and executive insight delivery. Partners cross-functionally to define meaningful KPIs, validate analytical outputs, lead analytics projects, measure business impact, and strengthen organizational analytical capabilities through training and methodological guidance.

Build and govern clinical analytics datasets, SQL transformations, data marts, dashboards, and reporting solutions for clinical quality, patient safety, outcomes, regulatory, and research initiatives. Partner with clinicians, executives, researchers, and enterprise data teams to define metrics, ensure data integrity, implement testing and governance frameworks, and deliver trusted executive, board, regulatory, and clinician-facing insights using modern cloud data platforms.

Collects, analyzes, and reports training, readiness, throughput, and trauma registry data. Develops dashboards, predictive analyses, quarterly readiness reports, and leadership visualizations. Ensures data accuracy, compliance, and consistency across systems; supports audits, inspections, accreditation reviews, and program evaluation; and recommends improvements to data collection and analysis methods.

Build and maintain dbt SQL models, data pipelines, curated datasets, reports, and dashboards supporting state partners, customers, Finance, Operations, and executives. Own external and internal Metabase environments, support the data warehouse, and establish consistent metric definitions across technical and non-technical teams. The role also requires analytics support, stakeholder communication, and experience with Airflow, Python, and Git-based workflows.

Leads the Data Engineering team, overseeing priorities, delivery, mentoring, and engineering standards. Manages scalable ETL/ELT pipelines, data integrations, streaming systems, data warehouses, and Azure-based platforms. Owns platform reliability, monitoring, incident response, capacity, cost optimization, compliance, release management, and continuous improvement. Partners with analytics, data science, and business stakeholders while guiding architecture, Agile execution, governance, security, and technical risk management.

Analyzes HR, statistical, and clinical data to identify trends, outcomes, and actionable insights. Prepares accurate reports and studies, maintains data integrations and databases, supports special projects, and partners with leaders. The role also focuses on data integrity, process automation, and developing on-demand descriptive analytics tools.

Designs and maintains operational data infrastructure for smart manufacturing, including pipelines, data warehouses, ETL/ELT processes, time-series data systems, integrations, governance, and trusted datasets. Uses SQL and Python to support reporting, analytics, automation, dashboards, and operational decision-making. Partners across manufacturing and enterprise systems, investigates complex data challenges, evaluates emerging technologies, and supports advanced analytics and digital transformation initiatives.

Designs, deploys, and sustains cloud-based analytics platforms and scalable data engineering solutions. Builds ingestion pipelines, transformation processes, storage architectures, APIs, and microservices for enterprise data collection and analytics integration. Applies cloud engineering, data management, security, governance, monitoring, and software development best practices. Requires collaboration with cross-functional teams and expertise in Azure, AWS, or GCP.

Enters, maintains, verifies, and audits participant program data, including intake forms, service records, case notes, demographics, and outcomes. Generates routine and grant reports, resolves data discrepancies, maintains confidential digital and paper records, and supports compliance, quality assurance, referrals, and administrative tracking. Collaborates with program staff and leadership to meet reporting deadlines and performance goals.