Top Data & Analytics Jobs

The Workforce Planning Analyst will develop workforce models, forecast demand, manage staffing levels, and produce reports to optimize workforce effectiveness in a global call center environment.

As a Senior Data Engineer, you will implement data ingestion patterns, build pipelines in Azure, and enhance development with AI tools, aiding the migration to a cloud-based architecture.

The Data Engineering Consultant will design and implement scalable data pipelines, develop data transformations using PySpark, optimize Databricks performance, and manage data orchestration and scheduling tools like Apache Airflow in the Azure ecosystem.

Design and maintain data pipelines, implement data integrations, mentor junior developers, and develop AI-powered solutions to enhance reporting and decision-making.

The Data Engineering Lead will develop and maintain data pipelines, optimize data platforms, ensure data integrity, and automate deployments while collaborating with various teams.

The Payor Contracting Analytics Director leads financial, analytical, and operational components of payer contracting, overseeing reimbursement modeling and identifying growth opportunities.

The Sr Manager of Payor Performance Analytics drives financial, analytical, and operational components of payer contracting, overseeing reimbursement modeling and ensuring successful contract negotiations and implementation.

Design, build, test and implement data solutions and pipelines; analyze reporting inventory; develop metrics, KPIs, reports and dashboards; optimize queries; build and maintain Azure data services and some on-prem SQL servers; engage stakeholders and lead projects to deliver measurable technology and process improvements.

Design, build, and operate Azure/Databricks lakehouse solutions and batch/streaming pipelines with automated data quality, governance, security, cost optimization, and Power BI semantic models for enterprise reporting.

Lead end-to-end data engineering: design, build, test, deploy, and maintain ETL/ELT pipelines and data platforms on Azure/Databricks. Drive data quality, governance, observability, ML/GenAI data pipelines (LLM/RAG/embeddings), API integrations, and best practices to enable analytics and AI solutions across healthcare domains.