Top Senior Data & Analytics Jobs in Hartford, CT

Lead design and execution of data migration strategies for Salesforce Revenue Cloud (CPQ & Billing). Define data architecture, mappings, and transformation logic; build SQL-based extraction and ETL processes; perform iterative test loads, reconciliation, and validation. Collaborate with clients and cross-functional teams to manage cutovers, documentation, and migration quality for quote-to-cash data.

Lead customer-facing analytics: build dashboards, reports, and POCs that demonstrate ROI and utilization trends for healthcare provider data. Collaborate with data science and engineering on advanced models, assess and integrate new data sources, ensure data quality, and support presales and executive-facing storytelling.

Lead the vision and execution of a scalable, multi-tenant data platform: own ingestion, warehouse, transformation, BI, and AI-on-data layers. Manage and grow a data engineering team, define engineering standards (CI/CD, infra-as-code, testing, lineage), productize integrations, and collaborate with Product, Engineering, and GTM for client onboarding and data delivery.

As a Data Engineer at Common Room, you'll build ETL pipelines, process billions of events daily, and collaborate on backend projects using AWS, Postgres, and Node.js.

Lead the architecture and design of an operational data platform, focusing on data unification, streaming integrations, governance, and mentoring teams while ensuring HIPAA compliance.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

Lead data conversion processes, provide expert guidance on Oracle Cloud, and ensure the successful implementation of conversion solutions while collaborating with stakeholders.

As a Data Scientist, you'll empower the company with data insights, develop metrics and experiments, and collaborate with various teams to drive product decisions.

Develop and maintain ETL solutions, optimize processes, validate data, and support production issues. Collaborate with analysts for efficient data integration.