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

The Principal SAP PaPM Configuration Engineer analyzes and configures use cases, supports production users, and mentors team members to enhance SAP PaPM systems within the finance environment.

Lead operational design and engineering for the data platform: own Snowflake and dbt administration, automate platform operations and CI/CD, monitor platform health and observability, enforce governance and access, optimize performance and costs, and develop AI/agent integrations to enable governed data access for business users.

Lead RevOps data modeling, ETL/DBT development on Snowflake, SQL-based analytics, and Tableau reporting. Optimize and maintain RevOps systems (Salesforce, Clari, Outreach, Gong/Chorus), ensure data quality, apply advanced analytics/AI concepts for forecasting, and partner cross-functionally to deliver actionable revenue insights.

Lead the development and implementation of data architecture strategies, mentor a team to deliver solutions, and collaborate with stakeholders to enhance resources while ensuring project success and quality outcomes.

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.

As a Senior Data Engineer, you'll design scalable data models, build automated ETL pipelines, and mentor junior engineers while collaborating across teams.

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.

The Principal Data Analyst will manage pricing and profitability strategy for Workhuman's E-commerce store, leveraging data analysis and cross-functional collaboration to drive decision-making and implement improvements in pricing strategies.

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.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.