Top Healthtech Data & Analytics Jobs

Leads Commercial data architecture and technology ownership across Commercial, Medical Affairs, and Patient Services. Defines data strategies, warehouses, data products, master data management, governance, quality standards, and analytics enablement. Partners with business stakeholders, Data & AI teams, vendors, and implementation partners to design scalable solutions using platforms such as Snowflake, Tableau, and Power BI. Provides architecture oversight, supports AI initiatives, manages technical delivery, and ensures data compliance, reliability, and operational sustainability.

Designs, develops, tests, and maintains BI reports, dashboards, data models, data warehouses, and ETL processes using Microsoft BI tools. The role analyzes source data, resolves data integrity issues, supports stakeholders and end users, implements data protection solutions, and maintains documentation. This is a fully remote position with approved-location restrictions.

Analyze large-scale electronic health record and real-world data using SQL, R, and Python. Scope requests, produce research studies and results, write Databricks SQL regex queries, support customers, investigate data sources, collaborate on peer-reviewed publications, and create enablement materials for researchers.

Lead the technical strategy and architecture for a scalable clinical data platform. Drive cross-team engineering initiatives, redesign legacy data pipelines, build batch and streaming systems, develop deployment and self-service tooling, improve monitoring, manage data models and governance, ensure privacy and security, and mentor engineers. Partner with product, AI, infrastructure, health systems integration, and business intelligence teams to deliver reliable, extensible data capabilities.

Cleans, analyzes, validates, and reports HIV program data from CAREWare, EvaluationWeb, surveillance, testing, prevention, and other sources. Develops data quality checks, resolves inconsistencies, matches datasets, supports reporting and quality management, provides technical assistance to subrecipients, troubleshoots data systems, and translates findings into actionable recommendations for public health leadership and programs.

Owns clinical data operations by building and maintaining ELT pipelines, warehouse models, data contracts, quality controls, reconciliations, dashboards, and monitoring. Integrates clinical, laboratory, sequencing, and corporate data into validated, audit-ready systems. Supports production reliability, partner data transfers, regulatory compliance, root-cause analysis, documentation, stakeholder collaboration, and technical guidance for research and development teams.

Own analytics for the clinician lifecycle, from recruiting and credentialing through performance, quality, retention, and business impact. Build operational scorecards, predictive retention models, licensing dashboards, and transcript-based empathy scoring frameworks using SQL, Python, BI tools, NLP, and LLMs. Partner with clinical, quality, operations, talent, product, and executive stakeholders to connect clinician behaviors and outcomes with patient retention, NPS, compensation, training, and workflows.

Design and support ETL, data migration, transformation, import, export, and validation workflows for moving legacy EHR data into athenahealth systems. Build Python and SQL utilities, define source-to-target mappings, support HL7 and FHIR interoperability, validate EHI exports, investigate data quality issues, document processes, and collaborate with product, implementation, operations, sales, and engineering teams in a remote environment.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Leads the design, development, maintenance, and implementation of complex ETL pipelines across structured and unstructured data sources. Establishes scalable, metadata-driven integration patterns, improves data quality and maintainability, performs root-cause analysis, and supports secure data solutions. Collaborates with stakeholders, maintains ETL platforms and cloud services, advances engineering best practices, and mentors team members.