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

Lead analytical monitoring and strategic analysis for homeowners insurance, translate findings into executive recommendations, present to senior leadership, partner across the business to drive profitable growth, and mentor junior team members.

Provide advanced analytical support to Enterprise Procurement by synthesizing large datasets, developing dashboards, and delivering insights to influence procurement strategy. Lead project workstreams, present recommendations to stakeholders, maintain reporting infrastructure, collaborate with data providers and business partners, and mentor teammates. Evaluate tools, processes, and apply AI/GenAI and automation to drive expense-saving opportunities and operational efficiency.

The Associate Principal will translate client needs into analytical specifications, ensure quality control of analytical outputs, and deliver clear insights while overseeing methodologies and clinical context research.

Help new Dynatrace customers adopt Digital Experience capabilities (Synthetic Monitoring, RUM, Session Replay). Perform data-driven analysis, create concise enablement and investigation deliverables, prioritize customer onboarding activities, drive usage expansion, and collaborate with account teams while communicating findings to technical and business stakeholders.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Lead RevOps data modeling, ETL/DBT development, and dashboarding to ensure high-quality revenue data. Build Snowflake data marts, author complex SQL, create Tableau visualizations, apply AI/ML forecasting, and partner with Sales, Marketing, Finance, and IT to resolve data quality and reporting issues.

This role focuses on post-sale technical execution, ensuring customer onboarding and deployment, driving customer consumption of products, writing production code, diagnosing issues, and expanding adoption across teams.

Lead and scale a casino analytics team to drive data-informed strategy, experimentation, and reporting. Partner with product, data science, and operations to deliver executive insights, build analytical frameworks, and develop high-performing analysts to unlock growth and operational efficiency.

Design and own end-to-end data models and dbt transformations on BigQuery, maintain the semantic layer in Lightdash, govern metrics, enable AI-assisted analytics workflows, partner with stakeholders to deliver trusted reporting, and lead data modeling standards, testing, and documentation.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Lead design and implementation of enterprise Product Information Management (PIM) solutions, ensure product data quality and integration, drive business development and client engagement, mentor team members, improve processes and productivity, and align product data management with organizational objectives.

Lead and architect end-to-end Master Data Management (MDM) solutions, manage client relationships and project delivery, mentor and coach team members, ensure data quality and integration, and align MDM platforms with business processes to improve data stewardship, taxonomy design, and model harmonization.

Design and implement data architecture and scalable ETL/ELT pipelines using cloud platforms (AWS/Azure/GCP). Develop data models, ensure governance and security compliance, analyze complex problems, mentor junior staff, build client relationships, and enhance technical skills to deliver high-quality data solutions.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.