Top Senior Data & Analytics Jobs in Hartford, CT

Lead measurement and insights strategies across B2B client programs. Analyze earned/social/web data, conduct secondary research, build measurement frameworks and dashboards, deliver client-facing recommendations, mentor junior staff, and advance agency analytics capabilities.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Deliver MSBI solutions using SSIS, SSRS and SQL Server; design BI solutions (including Tabular Model), manage offshore teams, enforce coding standards, perform SQL data analysis, conduct quality audits, and present insights to clients in a client-facing role.

Senior Talend developer responsible for developing and maintaining Talend ETL processes, performing data analysis and source-to-target mappings, designing and deploying ETL solutions, setting up ETL environments, and supporting data warehouse/OLAP architectures. Works with SMEs, follows technical and business requirements, and ensures data quality, metadata, and auditing.

The Data Modeler will focus on dimensional and operational modeling, data dictionary mapping, XML schema design, and liaising with clients. They will work on data profiling and utilize modeling tools while managing data artifacts and collaborating with external teams.

Build and maintain P&C actuarial pricing models and indication reports; refine pricing methodologies; analyze large datasets; automate workflows with Python, SQL, and Excel; create dashboards and presentations; collaborate with underwriters, claims, program teams, and reinsurers; and drive process and methodology improvements.

Lead design, development, and migration of enterprise SAP BW solutions to SAP Datasphere; architect hybrid data flows with Microsoft Fabric and Azure Synapse; integrate BW with Salesforce and SQL Server; embed AI (Copilot, Azure OpenAI) into analytics; manage deliverables, mentor offshore teams, enforce standards, and ensure data integrity and performance for reporting and analytics.

Lead design, development, and migration of enterprise data warehouse solutions from SAP BW/BW4HANA to SAP Datasphere. Architect data models and hybrid data flows with Microsoft Fabric/Azure Synapse, integrate BW with Salesforce and SQL Server, embed AI capabilities (Copilot, Azure OpenAI), manage offshore teams, enforce standards, and deliver Power BI reporting and analytics to business stakeholders.

Senior Data Architect contractor to accelerate and modernize the data platform: assess landscape, design end-to-end data solutions, define integration and metadata patterns, enable data mesh and cloud migration (AWS), and produce reusable architecture artifacts for handoff to engineering teams.

Design and govern conceptual, logical, and physical enterprise data models supporting analytics, reporting, AI-ready datasets, and certified data products. Translate business requirements into scalable data structures across customer, product, payer, and territory domains. Establish modeling standards, review models against Common Data Model standards, maintain metadata and lineage accuracy, and resolve data gaps and inconsistencies. Collaborate with business, engineering, and technology stakeholders to provide modeling expertise and design guidance.

Leads enterprise reporting for data quality, governance, compliance, and operational performance. Designs executive dashboards, scorecards, and reporting packages; integrates metadata and quality metrics; aligns definitions and thresholds with stakeholders; oversees incident and remediation tracking; manages vendors, schedules, documentation, and change controls; validates data integrity; automates recurring reports; and escalates risks and compliance issues to leadership.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and automation. Partner with governance, privacy, architecture, modeling, and platform teams to deliver reliable, compliant, AI-ready data products. Monitor operational performance and resolve pipeline and data reliability issues across complex enterprise environments.