Top Senior Data & Analytics Jobs in Boston, MA

Lead VoC and customer insights analyses by querying internal and external data, identifying trends, and producing dashboards and reports. Deliver data-backed recommendations, synthesize findings for senior stakeholders, and support CX initiatives with SQL/Python analysis and clear visual storytelling.

The VP of Alternative Data Strategy drives sourcing, prioritisation, and implementation of alternative datasets, aligning data opportunities with investment strategies and governing data usage across teams.

Lead RevOps data modeling, ETL/DBT development, and dashboarding to ensure high-quality revenue data. Build Snowflake data marts, author complex SQL, create Tableau visualizations, apply AI/ML forecasting, and partner with Sales, Marketing, Finance, and IT to resolve data quality and reporting issues.

Lead and mentor a data engineering team to design, build, test, and support cloud-based, real-time data platforms and distributed microservices using modern big data, streaming, and data warehousing technologies to deliver scalable customer and enterprise experiences.

Own and govern centralized data assets; design scalable dbt/Snowflake models; model Stripe subscription and payments data; set SQL standards, testing, monitoring and documentation; lead complex BI projects in Hex; partner with product, engineering, operations and GTM to deliver durable analytics solutions.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

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.

Designs and maintains production data pipelines, dbt models, Airflow workflows, and Snowflake datasets integrating Workday and other People systems. Owns data quality, observability, governance, row-level security, and access controls for sensitive People data. Builds semantic models and AI agents, collaborates with analysts and stakeholders, translates requirements into reliable data products, communicates technical trade-offs, and mentors other engineers.

Leads and develops a data engineering team supporting People Analytics and AI-assisted workforce analytics. Designs scalable data models, pipelines, semantic layers, testing frameworks, and governance practices. Remains hands-on with production code, reviews, and technical problem-solving while partnering with People Analytics, business, legal, and compliance stakeholders. Establishes engineering standards across Python, SQL, dbt, Airflow, Snowflake, CI/CD, data quality, observability, privacy, and security.

Design, build, and optimize modular dbt pipelines and data models; translate ambiguous product requirements into production-grade data assets; diagnose query performance and lower warehouse compute costs (including migration to Snowflake); enforce code hygiene, data security, testing, and peer review; mentor junior engineers and adopt AI-assisted development tools to speed test generation and legacy discovery.

Analyze administrative and clinical healthcare data to build reporting solutions, identify optimization opportunities, and support clinical program effectiveness. Apply statistical analysis, data mining, and predictive modeling to improve decision-making, patient outcomes, utilization, and cost efficiency. Develop dashboards and KPIs, monitor healthcare trends, collaborate with clinical, data science, engineering, and client teams, and lead complex multidisciplinary projects.