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

Design, build, and own the full data platform (ingestion, modeling, CI/CD, orchestration, observability, and BI). Implement streaming and batch pipelines for IoT data, enable governed self-service, enforce data governance/privacy/security, evolve AI access patterns, and provide technical leadership and mentorship to data engineers and data scientists to deliver production-ready analytics and ML capabilities.

Conduct quantitative research using surveys, experiments, and advanced statistical methods for healthcare and life sciences client engagements. Analyze data, develop insights and visualizations, support rigorous research design, and translate findings into actionable recommendations. Collaborate with consulting teams and global delivery groups while ensuring research quality and communicating complex concepts to technical and non-technical audiences.

Build and maintain large-scale data pipelines and analytics platforms for EDA datacenter observability, telemetry, reliability analysis, and capacity forecasting. Develop batch and streaming workflows, data models, quality frameworks, monitoring, and retention strategies using metrics, logs, traces, and hardware health data. Partner with observability engineers, data scientists, analysts, and infrastructure teams to deliver scalable, reliable, discoverable datasets for analytical and predictive use cases.

Analyze deposit portfolio, customer, and market data to identify growth opportunities and optimize banking products. Build performance dashboards, develop statistical models and business cases, support pricing and product initiatives, and enhance data structures with Data Management. Partner cross-functionally with Finance, Marketing, Technology, Treasury, and Retail Administration while providing strategic insights to senior management.

Leads digital analytics strategy across web, media, CRM, and marketing channels. Develops dashboards, reports, KPIs, forecasts, and actionable insights to improve digital performance, customer engagement, and business growth. Ensures data accuracy, communicates findings to stakeholders, identifies trends and opportunities, and supports analytics training. Requires collaboration across teams and familiarity with digital marketing, e-commerce or lead generation, and analytics platforms.

Supports client-facing portal data, reporting, dashboards, and visualizations. Translates business needs into requirements, mappings, user stories, and acceptance criteria; validates Power BI and Snowflake data; performs reconciliation and root-cause analysis; supports production incidents, releases, testing, and documentation; and coordinates offshore support partners across time zones.

Analyzes business requirements and defines functional specifications for small to moderate projects. Translates requirements into functional designs, test plans, documentation, and user materials. Coordinates with IT to resolve issues and improve business processes. Supports application testing through traceability analysis, test preparation, script writing, and functional test execution. May guide less experienced colleagues.

Designs, builds, and optimizes enterprise Databricks Lakehouse pipelines and data products using Spark, Delta Lake, SQL, and Python. Leads complex data initiatives, production support, governance, CI/CD, workflow orchestration, monitoring, and modernization of legacy SQL Server solutions. Partners with stakeholders, optimizes performance and cost, mentors engineers, and drives engineering standards across Azure data platforms.

Business Analyst partners with stakeholders and developers to analyze requirements, improve business processes, and implement IT system solutions. Responsibilities include functional documentation, data flows, end-to-end testing, User Acceptance Testing, application support, access issue resolution, reporting and visualizations, user training, and project participation. The role requires SDLC experience, business analysis or software implementation experience, strong communication, project management, and familiarity with Agile and waterfall methodologies.

Own executive reporting and data strategy for autonomous vehicle system performance. Lead the weekly Software Performance Review, develop board-level reporting, analyze robotics and autonomy metrics, translate technical findings into strategic recommendations, and establish data visualization standards. Partner cross-functionally across engineering and performance teams, create data-driven feedback loops, and mentor Business Analytics and Business Intelligence engineers.