Top Senior Data & Analytics Jobs

Design, build, and maintain scalable data pipelines, client integrations, and data models to support reporting, analytics, and AI/ML. Ensure data quality, monitoring, and reliable ingestion of healthcare (FHIR/HL7, EHR) and claims data. Collaborate with product, engineering, and AI teams to enable downstream products and analytics.

Serve as the day-to-day insights partner for an OTC and Personal Care client: lead analyses using syndicated NIQ data, translate findings into executive-ready recommendations, manage multiple projects, run client working sessions, and support business growth through proactive thought leadership. Requires strong storytelling, stakeholder management, and the ability to work onsite at least two days weekly in New Providence, NJ.

The AVP leads institutional effectiveness initiatives including assessment, accreditation, data analytics, and continuous improvement, advising senior leadership and ensuring alignment with strategic goals.

Design, build, and optimize end-to-end data pipelines and dataflows, integrate with AWS, maintain schemas/data dictionaries, provide Tier 3 support, collaborate with stakeholders and product teams, document architectures, and support off-hours deployments. Ensure data governance, scalability, and production readiness while working primarily on-site in a cleared defense environment.

Provide analytic and operational support for LEIMS: validate and analyze law enforcement data, produce trend and executive reports, coordinate stakeholders, deliver briefings, support help desk and system requirements, and assist with O&M and oversight responses.

Lead design, development, testing, deployment, and support of BI dashboards and data models (Qlik, Power BI, Excel). Build and optimize data visualizations, write complex SQL, collaborate with ETL teams, manage Qlik platform administration, provide L2 developer support, and lead cross-functional analytics and performance management initiatives to improve business operations.

Design and manage scalable data pipelines and infrastructure, implement ETL/ELT processes, and collaborate with teams to ensure data quality and accessibility.

Lead complex analyses and modeling to uncover drivers of performance, develop actionable insights and executive-level storytelling, own performance analyses, build decision frameworks, create dashboards, and mentor junior analysts to influence strategic business decisions.

Analyze multi-channel fraud trends, develop data-driven insights and recommendations to prevent and detect fraud, evaluate controls and authentication strategies, support testing and implementation of fraud controls, and present executive-ready analytics to inform enterprise fraud strategy and prioritization.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Lead design and implementation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and services to ingest, normalize, link, and version identity data. Ensure auditable matching, data lineage, quality checks, schema enforcement, access controls, and privacy-by-design. Collaborate cross-functionally with product, analytics, legal, privacy, and security teams and create documentation, monitoring, and runbooks.