Top Hybrid Data & Analytics Jobs in Boston, MA

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.

Provides individualized research and data consultations to Harvard Kennedy School faculty, students, and fellows. Identifies datasets, supports research design, methods, analysis, data management, citation tools, and reproducibility. Designs and delivers workshops, develops instructional resources, administers course technology licenses, manages access to licensed data and software, reviews data management plans, and embeds research and data literacy into courses and orientations.

Manages research data acquisition, licensing, contracts, vendor relationships, governance, and lifecycle management at Harvard Kennedy School. Leads data safety reviewers, develops compliant data management plans and SOPs, assesses risks involving sensitive and restricted data, and advises researchers and leadership on licensing, legal, regulatory, and security requirements. Coordinates with faculty, vendors, procurement, legal, compliance, library, and sponsored research offices while providing training and portfolio reporting.

Provides research and data consultations to Harvard Kennedy School faculty, students, and fellows. Identifies datasets, supports research design, methods, data analysis, data management planning, and reproducibility. Designs and delivers workshops and course-integrated instruction, administers student access to licensed research tools and software, and manages access to institutional data resources. Builds relationships across the HKS community to develop responsive research and data services.

Leads enterprise data integration and engineering capabilities, including APIs, middleware, ELT pipelines, data governance, master data management, and cloud analytics platforms. Designs secure, compliant integrations across ERP, CRM, clinical, research, quality, finance, and commercial systems. Establishes architecture standards, data quality controls, monitoring, validation, and support processes while coordinating internal engineers, vendors, and business stakeholders. The role also provides technical leadership for trusted datasets, regulatory compliance, operational reliability, and commercialization readiness.

Drive mobile app growth through ad-hoc SQL analysis, dashboards, and BI tools; partner with CEO/CFO to provide insights, streamline ETL/ELT pipelines, and optimize user acquisition, retention, and monetization.

Build and maintain cloud-native data pipelines, reusable data frameworks, and modeled datasets for analytics and AI. Implement data quality, monitoring, governance, testing, CI/CD, and performance optimization. Troubleshoot production issues, support incident response, and collaborate with data, analytics, finance, sales, and operations teams to deliver scalable enterprise data solutions.

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

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.

Owner of the semantic layer: build and maintain core data models and metrics, run dbt orchestration with CI/CD and testing, implement reverse ETL pipelines, and enforce PHI access controls to keep data HIPAA-compliant.

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.

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