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

Build and productize externally consumable data assets from concept to delivery. Define schema, governance, SLAs, documentation, and delivery (Snowflake share, SFTP, API). Partner cross-functionally to productionalize datasets, monitor quality, iterate on customer feedback, and create repeatable productization frameworks.

Lead enterprise healthcare data modeling: design and maintain conceptual/logical/physical models, integrate varied clinical sources, implement common data model transformations, monitor data quality, and collaborate with clinicians, data scientists, and engineers.

Lead architecture and delivery of master data management solutions, drive large projects, improve data quality and operations, design taxonomies, and mentor teams to achieve operational excellence and client satisfaction.

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 scalable cloud data infrastructure and pipelines to transform transactional and financial data into reporting-ready datasets. Ensure accuracy, traceability, governance, and observability; partner with cross-functional teams, mentor engineers, and leverage AI-assisted tools to improve engineering productivity and enable AI-powered applications.

Own end-to-end data pipelines and production-grade dbt models (Snowflake) for Sales and Product analytics. Build governed data marts, dimensional models, and reverse ETL workflows. Improve data quality, testing, monitoring, and documentation. Partner with GTM, Product, and BI stakeholders, mentor peers, and contribute to platform tooling (Airflow, Terraform, AWS) to enable reliable, scalable analytics.

Lead design and maintenance of data warehouse architecture, schemas, and ETL to support reporting and BI. Provide Oracle DBA support (configuration, backup, tuning), integrate enterprise systems (Workday, Cayuse, Lawson), enforce data governance and security best practices, and collaborate across IT to document and optimize data solutions.

Manages marketing technology, CRM data analytics, AI-enabled data enrichment, and data quality initiatives. Develops governance guardrails, standards, controls, and processes to maintain accurate data. Analyzes marketing and business development information to identify revenue and operational efficiency opportunities, creates recurring reports, collaborates with vendors and internal stakeholders, and implements tools that support strategic decision-making and demand generation.

Own client-facing data services projects for private markets and financial services clients. Responsibilities include onboarding clients, structuring data from multiple sources, managing data collection, preparing status reports, creating customized dashboards and reporting templates, handling client requests, supporting new product launches, and mentoring Associates. The role requires strong Excel and Microsoft Office skills, client service, communication, organization, and attention to detail.