Top Data & Analytics Jobs

As a Healthcare Analyst II, you will analyze healthcare data to optimize strategies, conduct quantitative analysis, and provide insights for clinical interventions, partnering with cross-functional teams.

The Senior Business Intelligence Engineer will design, build, and optimize data models and dashboards, ensuring data quality and supporting business decision-making through analytics.

Lead the design and delivery of a cloud-native healthcare data platform on AWS. Architect and implement scalable batch and near-real-time pipelines, lead Apache Iceberg lakehouse engineering, build reusable ingestion/transformation/validation frameworks, drive data quality, observability, and operational excellence, review architectures, conduct code reviews, mentor engineers, and collaborate across platform, analytics, and business teams.

Partner with stakeholders to gather and document data requirements, translate needs into user stories and technical specs, perform SQL-based data analysis, source-to-target mapping, and validation, support data quality, lineage, and monitoring, serve as primary requirements contact, contribute to Agile ceremonies, assist change management and rollout, and maintain operational and client documentation.

The role involves managing a team of data analysts to ensure the quality and usability of healthcare market datasets, implementing analytical standards, and translating complex data outputs into actionable business insights.

Build and maintain scalable, governed data pipelines from ingestion through transformation and integration. Implement schema validation, data quality checks, job monitoring, and production-grade APIs. Work with Python, SQL, Airflow, dbt, AWS (EMR, Athena, S3), Iceberg/Parquet, and contribute to CI/CD, observability, and on-call support while collaborating with analytics and product teams.

As a Data Engineer, you will develop and maintain scalable data pipelines using AWS, support data processing, and collaborate with teams to deliver high-quality data solutions.

Analyze large healthcare claims, provider, operational, and financial datasets to identify trends, anomalies, and inefficiencies. Build dashboards, automated reports, and forecasting models; monitor SLAs, throughput, and financial recoveries; perform invoice reconciliation and root-cause analysis. Partner with cross-functional teams to support strategic decisions while maintaining HIPAA-compliant data governance using SQL and Python.

Analyze healthcare claims, provider, financial, and operational data to identify trends, anomalies, and inefficiencies. Build automated reports, dashboards, and forecasts using SQL, Python, and BI tools to support audit, finance, and operations, ensuring data quality, SLA monitoring, and actionable recommendations.

Lead analytics for payment integrity by analyzing large healthcare claims and operational datasets, building automated reports, dashboards, and forecasts, monitoring SLAs and financial reconciliations, detecting process inefficiencies, performing root-cause analysis, and partnering with engineering, audit, finance, operations, and leadership to drive operational improvements and reporting accuracy while maintaining data governance and HIPAA compliance.