Top Remote Senior Level Data & Analytics Jobs in Boston, MA

The Lead Data Governance Specialist manages data integrity and accessibility across platforms, driving best practices, collaboration, and compliance in healthcare analytics.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

The Lead Data Analyst will define KPIs, analyze data trends, build dashboards, and support new product launches, requiring strong SQL and Python skills.

Design and implement scalable go-to-market intelligence workflows and automation. Define business requirements for reports and dashboards, partner with Product and Analytics, improve Data Cloud tool adoption, document processes, support integrations, and deliver automation-aligned pre-sales and client-facing materials.

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

The Senior Ad Ops Engineer develops and manages data products for marketing activation, focusing on data pipelines, quality validation, and integration with marketing platforms.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.