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

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

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.

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.

Senior Data Analytics Consultant who turns observability data into business insights for enterprise clients. Manage 4–8 accounts, present performance strategies to technical and executive audiences, perform ad-hoc analysis, configure Dynatrace, build reports and dashboards, enable clients, influence product roadmap, and improve internal processes. Occasional client and annual team travel required.

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.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.