Top Business Intelligence Jobs in Hartford, CT

Own and optimize the enterprise workforce management platform, including forecasting, scheduling, staffing, intraday performance, shift and PTO bidding, and schedule adherence. Analyze workforce and operational data, identify root causes, create trend and productivity reports, model ROI, and recommend staffing improvements. Partner with analytics and operations leaders, mentor real-time analysts and schedulers, and drive efficiency across service and clinical operations.

Build and maintain Tableau dashboards, define KPIs, validate data, and query large datasets with SQL. Analyze cross-channel marketing performance across paid media, CRM, ecommerce, web, and app channels. Translate findings into actionable business insights, recurring client reports, and executive-ready presentations. Collaborate with engineering, analytics, data engineering, and strategy teams while guiding stakeholders toward data-driven decisions.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Senior Database Analyst/Administrator responsible for database architecture, administration, performance, security, data modeling, warehousing, ETL, migration, and data integrity. Develops SQL Server database objects, dimensional models, enterprise data marts, BI dashboards, and Splunk monitoring reports. Collaborates with stakeholders to translate business needs into technical requirements, supports Agile development, conducts code reviews, and implements cloud and hybrid-cloud database solutions.

Develops business intelligence and analytics solutions, including reports, dashboards, data marts, metadata layers, and decision-support applications. Analyzes data needs, designs dimensional and relational models, evaluates BI technologies, creates architecture documentation, and supports production troubleshooting. Partners with business and IT teams, manages small to midsize project scopes, establishes development standards, and mentors BI and analytics staff on tools, design practices, and data modeling.

The Sr. Data Analyst will utilize industry knowledge to analyze data, develop solutions, and support customers globally, focusing on delivering high-quality IT services.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead enterprise data architecture across multiple SaaS products by unifying reporting platforms, data models, and analytics capabilities. Assess current systems, define target-state architecture, establish data governance and quality standards, separate analytical workloads from transactional systems, and develop phased migration roadmaps. Guide database, engineering, and BI teams on cloud platforms, integration, modeling, performance, security, and reliability. Enable trusted cross-product reporting, governed self-service analytics, and data foundations for AI and advanced analytics.

Design, develop and maintain QlikView reports, models and dashboards. Work on end-to-end DW/BI tasks (ETL, data modeling, reporting), performance tuning, UI design, troubleshooting, and provide technical analysis while communicating with stakeholders.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Act as a strategic partner to Revenue Operations by analyzing performance, building executive dashboards and reports, improving CRM data quality and governance, supporting forecasting and pipeline management, and designing scalable processes and automations to increase efficiency and revenue visibility.

Lead data product strategy and governance for customer-facing reporting within Managed Services. Own reporting product roadmap, data quality, standards, delivery platforms (Redwood Insights, BI, Snowflake, Excel), implementation readiness, and cross-functional alignment to scale trusted, automated customer analytics and reduce manual reporting.

The Insights Architect will lead architecture initiatives, focusing on data quality, data mining, business intelligence, and big data environments in healthcare and insurance.

The Insights Architect will lead architecture design for data warehousing and big data environments, ensuring data quality and implementing best practices across diverse technical teams.

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Design and build Power BI reports and SSRS reports, write advanced SQL to extract and validate data, create scalable data models, investigate trends, automate reporting processes, and collaborate with business partners to translate requirements into usable analytics solutions.

Build and maintain performance dashboards, KPIs, and data frameworks for revenue operations. Analyze funnel performance and program effectiveness, translate complex data into leadership insights, automate recurring reporting, and perform SQL-based data wrangling and transformations. The role partners with cross-functional, engineering, and data science teams to improve measurement, resolve data issues, and support strategic business decisions.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design, build, and maintain Data Vault 2.0 data warehouse and Power BI solutions. Develop ETL pipelines, data models, reusable datasets, and data governance. Perform profiling, cleansing, migrations, and collaborate with infrastructure teams to optimize data delivery, automation, and reporting.

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.