Top Remote Senior Level Data Engineering Jobs in Boston, MA

Lead architecture and implementation of scalable batch and streaming ETL/ELT pipelines, data services, and graph-serving models for Observability & Insights. Own technical strategy, drive performance and cost improvements, enforce data governance and observability, lead cross-team initiatives, participate in on-call and incident follow-through, and partner with product and engineering to deliver low-latency graph exploration at extreme scale.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

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.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

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.