Top Data & Analytics Jobs

Develop and maintain large-scale ETL data pipelines, integrate and transform data from diverse sources, enforce data governance and quality standards, and monitor pipeline reliability. The role requires advanced SQL, Python, software engineering, DevOps, Git, CI/CD, troubleshooting across billions of records, and collaboration with business and technical stakeholders to design and support data solutions for healthcare analytics.

Designs, develops, deploys, and supports scalable cloud data engineering solutions for HEDIS processing and healthcare quality reporting. Builds ETL pipelines, data integrations, SQL transformations, and AI-enabled workflow automation. Collaborates with stakeholders, auditors, and product teams to ensure data quality, regulatory compliance, and operational reliability. Troubleshoots production issues, supports cloud modernization, applies CI/CD and testing practices, and mentors engineers as a senior individual contributor.

Leads a team of data engineers and subject matter experts delivering cloud-based data pipelines, AI-enabled workflow automation, and operational maintenance for HEDIS programs. Oversees cloud migration, regulatory reporting, quality measure compliance, stakeholder and auditor communications, technical architecture, production readiness, and service-level commitments. Mentors team members, resolves cross-functional dependencies, evaluates enterprise AI tools, and ensures scalable, reliable data engineering delivery across healthcare insurance data domains.

Leads target-state data architecture and strategy for a healthcare business line. Translates business needs into data models, governance, platforms, and reference architectures; directs pilots and proofs of concept; guides engineering teams; evaluates generative AI, semantic, metadata, knowledge graph, and vector technologies; and establishes standards for data quality, privacy, security, compliance, and responsible AI adoption.

Owns enterprise data architecture and engineering standards across cloud data platforms. Leads data modeling, ELT/ETL pipelines, Spark processing, Airflow orchestration, performance optimization, data quality, governance, security, and operational monitoring. Develops architecture roadmaps, ensures reliable analytics-ready data products, and mentors engineers through technical direction, design reviews, and architecture governance.

Leads enterprise data warehouse, reporting, analytics, and transaction-processing architecture and modernization. Designs scalable on-premises and cloud solutions, modernizes ETL and SQL into Python automation, oversees BI delivery, and establishes DevOps and CI/CD practices. Provides hands-on technical leadership across development, testing, deployment, performance, security, and support. Leads proof-of-concepts, produces architecture documentation, presents recommendations, and mentors architects, engineers, developers, analysts, and testers.

Designs and operates scalable batch and streaming data platforms supporting analytics, machine learning, and generative AI. Builds ingestion, ETL/ELT, orchestration, data quality, observability, governance, and lakehouse solutions. Partners with stakeholders on technical roadmaps, enables AI/ML workflows, improves platform scalability and cost efficiency, reviews engineering work, and mentors engineers.

Analyze, forecast, and report workforce and operational metrics (volume, AHT, shrinkage, occupancy, attrition, SLAs). Support short- and long-term capacity planning, develop business solutions, and present findings to drive operational decisions.

Leads the analytics strategy, roadmap, growth agenda, and portfolio expansion for Retrospective Coordination of Benefits and Reverification. Partners with Product, Operations, Technology, Growth, and Analytics teams to identify use cases, build business cases, measure financial and operational value, and drive adoption of predictive analytics, GenAI, and Agentic AI solutions. Advises senior leadership and resolves complex business challenges through enterprise-scale analytics initiatives.

Ensures the accuracy, integrity, and compliance of pharmacy, drug, pricing, prescriber, and related data. Performs audits, resolves data issues and service tickets, coordinates vendor enhancements, produces usage and impact reports, and supports data restructuring projects through implementation, testing, and validation. The role also provides reporting and data-extract consultation while managing multiple projects and deadlines.