Top Healthtech Data & Analytics Jobs

Manages donor database administration and data integrity using Blackbaud Raiser's Edge NXT. Oversees gift and constituent data entry, verification, imports, updates, receipting, acknowledgements, queries, exports, custom reports, segmented lists, and fundraising-related systems. Collaborates with Finance to integrate Raiser's Edge and Financial Edge for revenue reporting and gift processing. Serves as the internal specialist and primary contact for donor data systems.

Supports the Mission Critical team by analyzing operational data, identifying inefficiencies and root causes, and developing dashboards, visualizations, KPIs, and executive insights. Designs process and technology improvements, monitors adoption, creates SOPs and training materials, and collaborates with data engineering, field technology, project teams, and leadership to implement scalable solutions.

The Product Analyst will manage the product experience, consult clients, collaborate with internal teams, and guide new features in biotech and pharma contexts.

Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.

Lead and support actuarial data projects: investigate and extract data, validate reports, address data quality, modify SQL/SAS/4GL programs, produce tabular/graphical outputs, communicate results, coach team members, and participate in project leadership and data-system decisions.

Design, build, and maintain scalable data pipelines and architectures (ETL, data lake, MDM) using Snowflake and Talend Cloud. Ensure data quality and governance, enable AI-readiness, pilot AI/ML proofs-of-concept, support reporting (Tableau/Power BI), and manage data operations and external vendors.

Design, implement, and maintain ETL pipelines and data movement between on‑premises systems and cloud platforms (Microsoft Fabric). Use low-code/no-code tools, AI, and automation to deliver real‑time reporting and analytics. Monitor performance, test and validate data flows, integrate SaaS and on‑prem systems, document solutions, and collaborate with IT, researchers, and business units to meet data requirements and improve processes.

Design and maintain ingestion pipelines for 835/837 and scanned EOBs: OCR, LLM-assisted extraction, integrations (SFTP, clearinghouses), data modeling, validation, and reconciliation to produce deterministic, trustworthy healthcare records.

The Analytics Engineer will build data models and pipelines for reporting and analytics, improving data infrastructure for ML and AI products, and setting processes for data collection and analysis.

Lead architecture and implementation of an AWS-native data platform powering analytics, ML, and AI workflows. Build scalable ETL/ELT pipelines (Airflow, Fivetran, dbt), enforce governance, observability (Datadog), and data quality, and provide technical leadership across Data Science, Analytics, Product, and Engineering.