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

Analyzes complex regulatory data requests across insurance data sources, translates ambiguous guidance into precise requirements, collaborates cross-functionally, and delivers defensible findings. Builds reporting for leadership, documents data logic, and improves processes through automation, AI-assisted analysis, and reusable data practices. Leads projects independently and serves as a trusted expert in underwriting data and business processes.

Build and operate production data pipelines, models, and data products supporting finance, accounting, treasury, compliance, and regulatory reporting. Partner cross-functionally to define requirements, model on-chain and internal data, and ensure data reliability through reconciliation, quality checks, monitoring, and alerting. Use SQL, Python, cloud data warehouse, Airflow, dbt, and AI tooling. Mentor engineers, review technical work, document systems, and communicate data concepts to technical and non-technical audiences.

Build and maintain production data pipelines, dbt models, Airflow workflows, and governed datasets supporting People Analytics. Integrate Workday and other HR systems into reliable Snowflake data products, implement data quality monitoring, row-level security, semantic models, and AI agents. Partner with engineers, analysts, data scientists, and business stakeholders to deliver trusted data solutions, communicate technical trade-offs, enforce governance, and mentor other engineers.

Own the people analytics roadmap, build reliable HR data pipelines and reporting, and deliver workforce, talent, and process insights. Analyze employee lifecycle operations, measure performance, identify automation opportunities, and develop dashboards and predictive analyses for senior leaders. Partner across People, HRIS, IT, Finance, Legal, and data teams to improve data governance, privacy, operational efficiency, and employee experience. Establish analytical standards and coach People colleagues on data-driven decision-making.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Lead complex data analysis across Liftoff’s supply-side business, using optimized SQL on large-scale datasets and BI tools to build dashboards, reporting pipelines, and actionable insights. The role conducts root-cause analysis, evaluates experiments, translates technical developments into business impact, leads cross-functional initiatives, and mentors analysts. It partners with Engineering, Product, Data Science, Finance, Commercial teams, and executive leadership to influence roadmap and operational decisions.

Own Eve’s data platform end to end, including ingestion, orchestration, incremental dbt models, Snowflake administration, Terraform infrastructure, observability, access controls, and pipeline reliability. Build schema-change detection, freshness SLAs, CI environments, and incident processes while managing performance and compute costs. Partner with analytics engineers and stakeholders to maintain trusted data for reporting and AI systems, using AI-assisted development and documenting platform standards.