Top Remote Senior Level Data Engineering Jobs in Boston, MA

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.

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

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.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

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.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.