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

Partner with Finance, Accounting, and Revenue Operations to design and deliver Power BI analytics, semantic models, and decision support for forecasting, close, revenue, and spend analysis. Translate finance concepts into metrics, reconcile data across systems, collaborate with data engineering, and apply AI-assisted tools to automate and scale finance analytics for executives and business partners.

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.

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.

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.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

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.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.