Top Senior Business Intelligence Jobs in Hartford, CT

Designs and maintains business intelligence solutions, including dashboards, reports, data models, and visualizations. Performs complex data analysis, resolves technical challenges, translates stakeholder requirements into technical solutions, ensures data quality, and optimizes BI performance. The role requires advanced SQL, Power BI, Power Apps, large-scale data experience, healthcare data knowledge, and strong communication skills. It is remote with occasional office travel.

Lead cross-functional analytics initiatives delivering accurate, trusted dashboards and metrics. Partner with Sales, Operations, Product, and Data Engineering to align analytics with business strategy, solve ambiguous problems, and mentor junior analysts.

Ensure integrity and governance of reporting databases; develop automation frameworks and ETL processes; prepare data for BI; conduct code and periodic reviews; create data policies and documentation; collaborate with stakeholders to enforce data management practices; perform data, gap, and root-cause analysis; maintain performance and adopt new technologies.

Own end-to-end marketing and business intelligence: build automated dashboards (Domo), query large datasets (SQL/Snowflake), report subscription funnel economics, analyze channel performance and A/B tests, troubleshoot data anomalies, and partner with leadership to set KPIs and prioritize analytics work.

Support and develop BI applications for a client financial platform across environments. Build reports, analytics, and budgeting solutions (TM1), develop/tune Oracle SQL/PLSQL, deploy BI tooling, support UIs (low-code), follow Agile practices, and collaborate on integrations, security hardening, and operations.

Lead cross-functional analytics to inform clinical and operational decisions: build Tableau dashboards, create dbt analytical models, analyze large healthcare datasets (claims, EHR, HIE) with SQL, respond to ad-hoc requests via JIRA, and collaborate with product and engineering to improve data capabilities.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Build governed gold-layer data models and a single-source metrics layer in Snowflake (dbt); create and optimize dashboards in enterprise BI tools; use AI coding agents and AI-assisted tooling to accelerate development; ensure data quality, governance, and consistency; collaborate with data engineering and stakeholders to deliver trusted analytics for internal and client-facing use.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Validate and QA data across UI and API sources, investigate issues, manage taxonomy mismatches, compile non-automated reports, and update/maintain dashboards (Power BI/Tableau). Collaborate with Business Strategy, Investment, and Analytics teams to resolve data and KPI anomalies.

Design, develop, and deploy Power BI reporting and analytics on Snowflake. Migrate OBIEE reports to Power BI, build data models and ETL/ELT pipelines, write DAX and SQL, optimize report performance, ensure data quality, and support stakeholders with documentation and ongoing support.

Design, build, and maintain enterprise Power BI dashboards and data models. Integrate multiple data sources, write DAX, ensure data quality and performance, support stakeholders with requirements, documentation, governance, and ad hoc analytics to enable operational and executive decision-making.

The Director leads Business Intelligence efforts, advancing data solutions, managing teams, and ensuring reliable analytics for decision-making across the University.

Lead design, development, and maintenance of BI solutions (dashboards, reports, datasets). Partner with product, actuarial, underwriting to source and validate data. Automate reporting, perform audits/reconciliations, communicate findings to stakeholders, and mentor analysts. Act as Power BI SME and apply AI tools to accelerate development, code generation, automation, and QA.

Own and build Power BI reports and client-facing intelligence products within Microsoft Fabric. Develop DAX measures, campaign pacing and budget alerting, monitor contact data health and data delivery pipelines, transition vendor-built platforms in-house, and partner with IT/Data Engineering and cross-functional teams to ensure reliable, actionable reporting for Digital leadership and clients.

Design and implement scalable data platforms, build ETL/ELT pipelines, integrate multiple data sources, define KPIs, create dashboards and executive reports, ensure data quality/governance, and collaborate with stakeholders to optimize BI capabilities.

Lead BI reporting and advanced analytics to optimize marketing campaigns and ROI. Build dashboards, manage multi-source data, ensure data governance, provide actionable insights, mentor juniors, and partner with cross-functional teams to guide strategy.

Lead BI partner for product teams to design and maintain scalable data pipelines, dbt transformations, data marts, and observability. Translate business needs into analytical frameworks, support A/B testing and ML feature engineering, collaborate on data governance, and champion CI/CD and best practices for analytics engineering.

Lead QA for a reinsurance data warehouse and BI environment: design master test plans, validate complex data transformations, implement automated data tests (Snowflake/ADF), reconcile Power BI reports to sources, lead QA analysts and UAT with business stakeholders, produce audit-ready test evidence, and ensure data access/masking and regulatory compliance.

Lead cross-functional analytics and reporting efforts: build and maintain dashboards and automated reports, extract/clean large datasets from ERP/eCommerce/operational systems, define KPI governance, support forecasting and budgeting, improve data pipelines, and deliver actionable insights to inform strategic and operational decisions.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

Design, develop, and maintain BI dashboards, self-service reporting, and predictive analytics for a cloud-based federal case management program. Translate business requirements into technical designs, implement SQL/data transformations, ensure governance and compliance, support AI/ML capabilities, and drive adoption and performance of analytics solutions.