Top Hybrid Data & Analytics Jobs in Boston, MA

Build and maintain the company-wide data foundation for FinOps; develop pipelines, dashboards, and operating scorecards; support stakeholders across commercial, finance, clinical ops, and operations; validate metrics with analytics engineers; transform messy datasets into actionable insights and adopt AI-powered workflows to improve efficiency.

The role involves leading the IT compliance and CSV/CSA framework, ensuring regulatory compliance, managing audits and inspections, overseeing validation activities, and partnering with various stakeholders.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

Design, build, optimize, and support an AI-forward data platform. Develop scalable ETL/ELT pipelines using Databricks, Python, and PySpark. Build cloud-native solutions on AWS/Azure, apply CI/CD and secure development practices, collaborate with data scientists and stakeholders, and incorporate AI tools to improve engineering productivity.

Turn complex data into actionable insights for National Accounts by performing statistical analysis, forecasting, modeling, and automated reporting. Build dashboards and executive presentations, diagnose data quality, partner with account teams, data engineers, and finance to influence decisions and track performance metrics.

Build, test, and support Databricks Lakehouse pipelines using Spark, Delta Lake, Python, and SQL. Develop notebooks, jobs, and reusable components; manage data ingestion and integrations with on-prem SQL Server and SaaS systems. Implement data quality, governance, monitoring, CI/CD, and platform administration while partnering with analysts, data scientists, and stakeholders to deliver analytics-ready datasets.

Design, build, and operate scalable data platforms and pipelines ingesting radar sensor data. Implement ingestion, transformation, enrichment, aggregation, and publishing workflows across relational, NoSQL, time-series, and lake/warehouse systems. Optimize PostgreSQL performance, ensure data quality, observability, and collaborate with engineering, product, and infrastructure teams to enable AI and analytics.

Support and lead Pre-Award initiatives including process mapping, operational analysis, data modeling, KPI assessment, change management, and project management. Develop policies, training and communications, present findings to leadership, and coordinate cross-functional stakeholders to improve sponsored research administration.

The Sr. Analyst II will extract and analyze data insights, assist clients in understanding metrics, support project goals, and improve client service.

Lead the design and evolution of the enterprise data platform, establish standards, mentor teams, and collaborate across departments to deliver high-quality data products.