Top Hybrid Data & Analytics Jobs in Boston, MA

Designs, develops, and maintains enterprise ETL solutions using Informatica, SQL, cloud platforms, and data warehousing practices. Builds scalable data pipelines, integrates Salesforce and other enterprise systems, monitors data quality and performance, troubleshoots issues, and supports cloud modernization. Collaborates with business and technology teams in a regulated financial services environment while contributing to technical standards, documentation, governance, and mentoring junior developers.

Owns the Source-to-Pay data and analytics foundation, including master data, taxonomy, governance, quality, analytics products, automation, and AI readiness. Leads business requirements, operating models, executive dashboards, KPI frameworks, decision-support insights, and cross-functional platform enablement. Partners with Procurement, Finance, Legal, Risk, IT, and enterprise data teams to improve data reliability, controls, reporting, self-service analytics, and scalable automation.

Leads end-to-end analytics projects for FINRA’s regulatory operations, including scoping quantitative methods, developing predictive pipelines, expanding data sources, and delivering analytics capabilities. Promotes advanced analytics adoption, supports cross-market surveillance, engages stakeholders, responds to research requests, and mentors analysts. Requires collaboration across delivery teams and participation in strategic analytics initiatives.

Build and maintain scalable data pipelines, models, and cloud infrastructure supporting business performance analysis. Collaborate with data scientists, ML engineers, product teams, and business stakeholders to translate requirements into technical solutions. Develop self-service data tooling, optimize Snowflake and AWS environments for scale and cost, and support deployment through CI/CD and DevOps practices. The role also involves data integration, modeling, documentation, and ensuring data integrity across global entities.

Principal technical leader responsible for architecting and operating relational data marts, dbt data products, semantic layers, and shared data services. Builds scalable solutions in Databricks, Delta Lake, and Spark; owns data products through testing, deployment, documentation, monitoring, and support. Establishes governed metrics, data quality, lineage, observability, and access controls while partnering cross-functionally to resolve ambiguity. Mentors engineers, improves reusable frameworks, and supports BI, data science, and AI use cases.

Build and own analytical data products, dbt models, semantic layers, shared metrics, and data quality systems. Model GA4 and digital analytics data, activate trusted data through reverse ETL, and partner with analysts, product teams, and business stakeholders to support decisions. Mentor engineers and analysts, establish modeling standards, and contribute to self-service and AI-assisted analytics foundations.

Leads catastrophe risk modeling and analysis using exposure data, natural hazard information, geospatial techniques, and catastrophe models. Develops dashboards, reports, automation, and analytical tools to assess disaster impacts, support underwriting and pricing, inform portfolio strategy, and guide risk decisions. Partners cross-functionally, supports event response and regulatory filings, evaluates modeling technologies, and provides expertise on catastrophe risk and insurance applications.

Develops and maintains healthcare and research databases using SAS and SQL. Responsibilities include data cleaning, management, variable creation, database linking, analytic dataset development, software documentation, and supporting researchers with programming and data access. The role works with complex electronic health record, administrative claims, and other large datasets in UNIX and Windows environments, while collaborating with faculty, postdoctoral researchers, students, and external partners.

Designs and leads enterprise database architectures, data models, integrations, governance, and performance initiatives. The role supports scalable and secure SQL Server environments, cloud platforms, data warehouses, ETL processes, reporting, analytics, and transportation safety data systems. Responsibilities include optimization, security, backup and recovery, documentation, technical standards, and collaboration with software engineering and business teams. The position requires strong relational database, SQL development, administration, and enterprise data modeling expertise.

Design and scale reliable data platforms, pipelines, Java microservices, APIs, and reporting infrastructure. Build data validation and reconciliation workflows, support distributed systems, improve pipeline performance and resiliency, and partner with engineering, analytics, and business teams. Contribute to cloud-native infrastructure, CI/CD, Docker, Kubernetes, dashboards, and self-service reporting modernization.