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

Own the roadmap and backlog for insurance pricing tools, gather requirements, coordinate delivery, and develop scripts and processes across rating programs. Analyze premium mismatches, maintain SAS pricing tools, conduct pricing analyses and quality checks using Python, SAS, Excel, and related technologies. Collaborate with cross-functional teams, resolve defects, present findings, train colleagues, and support successful pricing model rollouts.

Designs and maintains business intelligence tools, dashboards, and data extraction processes. Performs source-system analysis, data profiling, ETL, data mapping, transformation-rule definition, testing, and dashboard performance troubleshooting. Uses SQL, Tableau, Alteryx, R, Python, SAS, Google Analytics, and Adobe Analytics to generate insights, predictive models, and reporting. Collaborates with business users and operations teams on user acceptance testing, deployment, and process improvements. The role is fully remote within the United States.

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.

Build scalable, secure data pipelines, models, platforms, and governance systems that enable AI applications to access trusted enterprise data. Partner with analytics, marketing, and product teams to translate requirements into technical solutions, independently deliver projects through production, and support sensitive-data security and access controls. Preferred experience includes LLM architectures, cloud data platforms, infrastructure as code, regulated environments, and technical leadership.

Own the enterprise reporting strategy and Sigma BI platform, including administration, governance, security, data modeling, dashboard development, and self-service reporting. Partner with business and analytics teams to define KPIs, create root-cause reporting frameworks, connect operational metrics to business outcomes, and improve reporting consistency. Lead Sigma adoption through training, documentation, standards, and mentorship while integrating modern data and AI technologies.

Serves as an enterprise architecture subject matter expert within a DoD environment. Supports DoD Business Enterprise Architecture initiatives, business process alignment, enterprise strategy, stakeholder analysis, requirements documentation, reporting, and project activities using MEGA HOPEX and Microsoft Office tools.

The Analytics Engineer will analyze sales proof-of-concepts and self-service trials, support growth and product-led sales initiatives, and evaluate pricing and monetization strategies. The role partners cross-functionally, models data in dbt, maintains data warehouses and ELT pipelines, experiments with emerging data and AI tools, and trains teammates on effective data workspace practices.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.