Top Healthtech Data & Analytics Jobs

Lead Allara’s data engineering strategy and build a reliable, governed data platform. Initially, the role focuses on stabilizing ETL pipelines, consolidating data models, closing source-data gaps, implementing quality monitoring, and establishing canonical metrics. Longer term, the director will own data governance, HIPAA-compliant access controls, AI-ready data infrastructure, self-service analytics, and development of the data engineering team.

Own Teal Health’s data warehouse, Fivetran ingestion, dbt transformation layer, and Omni semantic data models. Build reliable pipelines, integrations, tests, documentation, and layered warehouse models across marketing, product, operational, and healthcare data. Partner with Analytics on dashboards, establish data standards, troubleshoot source and schema issues, and manage ticket-driven priorities while protecting sensitive health data under HIPAA practices.

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Builds business-critical dashboards, scorecards, reports, and ad hoc analyses using SQL, Python, Excel, Power BI, and Tableau. Analyzes KPIs, identifies trends and root causes, automates recurring reporting, validates data, and translates complex findings into actionable insights for stakeholders and leadership. The role collaborates with data engineers and cross-functional teams to improve reporting workflows, data pipelines, and decision-making.

Design and build integrations connecting legacy practice management systems to an AI platform. Responsibilities include AI-assisted schema mapping, data modeling, ETL pipelines, REST/SOAP APIs, data cleansing, quality monitoring, production troubleshooting, documentation, and collaboration across architecture, product, engineering, and operations teams. The role requires applying LLM tools to schema inference, field reconciliation, anomaly detection, and data-quality automation while handling healthcare data securely.

Advise Sales leadership through advanced commercial analytics, predictive insights, dashboards, forecasting, territory planning, and AI-enabled decision tools. Analyze large multisource datasets, ensure data governance, optimize SQL and data architecture, and translate complex business questions into executive-ready recommendations. Partner with Sales, Marketing, Finance, BI, and IT to improve revenue execution, analytics adoption, and commercial performance while evaluating responsible AI use cases.

Designs, builds, operates, and modernizes secure ETL/ELT data pipelines for public health interoperability. Responsibilities include using NiFi, Kafka, Python, and SQL; deploying pipelines on Azure or AWS; implementing CI/CD with GitHub Actions; monitoring with Grafana; troubleshooting production systems; supporting legacy migrations; and ensuring data security, compliance, scalability, and reliability. The role collaborates with architects, integration engineers, data scientists, DevOps/SRE, and product teams.

Build, deploy, operate, and improve Databricks Lakehouse pipelines integrating SAP ECC, Microsoft Dynamics GP, Salesforce, and other systems. Develop medallion architecture, data models, quality checks, governance, security controls, documentation, and CI/CD workflows. Monitor reliability, freshness, performance, and compute costs; resolve failures and support downstream BI and AI use cases. The role also manages partner knowledge transfer, contributes to integration design, and mentors junior or outsourced engineers.

Owns governance, quality, integrity, and operational management of contract and customer master data. Oversees contract configuration, pricing controls, member onboarding, eligibility, roster management, exception resolution, metrics, and process documentation. Leads continuous improvement using Lean and Six Sigma methodologies, develops standardized controls, and manages a data operations team while collaborating with Sales, Finance, Reconciliation, IT, and other functions.

Leads Anovo’s enterprise data, analytics, and AI strategy, including AWS and PostgreSQL architecture, governance, data quality, reporting, predictive analytics, and responsible AI. Oversees data engineering, architecture, analytics, and data science teams; manages budgets, vendors, roadmaps, and investments. Partners with executives to define KPIs, improve patient and client outcomes, enhance operational and financial performance, and deliver governed dashboards, data products, and actionable insights.