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The Analytics Engineer builds and maintains data models for analytics, ensuring data quality and enabling self-service insights for analysts across the organization.

Embedded technical lead for Finance systems: design, build, and maintain integrations (NetSuite, ADP, Databricks), deploy AI-assisted finance automations, manage contractors, ensure HIPAA-compliant data handling, run high-priority technical projects (reporting migration, PO system, client portal), and maintain a prioritized engineering backlog.

The Senior Data Engineer will design and implement scalable data pipelines, ensure data quality, collaborate on data models, and support business needs using cloud platforms and integration tools.

The Data Engineer II will design and implement scalable data pipelines, collaborate with stakeholders, ensure data quality, and support analytics by utilizing cloud platforms and big data technologies.

Design and implement scalable data pipelines, support data ingestion and quality, collaborate on data models, and maintain data exports, contributing to technology improvements.

Build and own member-facing features across web, mobile, and backend services. Contribute to system design, performance, accessibility, and maintainability. Integrate .NET/C# backend services with Azure, collaborate across product, design, and engineering, participate in code reviews, mentor teammates, and help deliver reliable, scalable member experiences.

Build end-to-end conversion and funnel measurement for mid/lower funnel, create dashboards and attribution frameworks, analyze drop-offs and agent performance, generate actionable insights for operations, document methods, and automate reporting using AI tools.

Lead engagement analytics to measure and improve member funnel conversion. Own reporting infrastructure, drive ad hoc and cohort analyses, define funnel methodology, ensure data QA, apply automation and AI-assisted tools, and partner with Member Services and Operations while managing and mentoring analysts.

Partner with Client Success leadership to drive strategy and operations: capacity modeling, quota setting, OKRs/KPIs, forecasting, operating cadence for renewals/upsells, customer health scoring, and cross-functional project management. Collect Salesforce and data requirements and ensure successful implementation to enable scalable client launches, retention, and expansion.

The Senior GRC Engineer will develop compliance infrastructure, automate evidence collection, oversee AI governance, and ensure healthcare compliance, primarily through coding and integration.