Top Analysis Reporting Jobs in Hartford, CT

Analyze performance marketing and subscription-funnel data, including acquisition efficiency, conversion, retention, churn, and customer lifetime value. Build automated Domo dashboards and governed reporting pipelines from multiple data sources. Investigate data anomalies, analyze A/B tests, define KPIs, and communicate insights to executives. Partner with marketing, product, engineering, finance, agencies, and BI contractors while independently executing analytics projects and improving reporting workflows.

Leads consumer and market insights for Yahoo Ads, partnering with sales and go-to-market teams to develop data-driven narratives, audience profiles, vertical trends, case studies, and client materials. Uses Yahoo first-party data, syndicated research, quantitative and qualitative methods, and generative AI tools to accelerate research. Builds validated analytical templates and self-service resources, collaborates on reporting pipelines and dashboards, and translates complex findings into executive-ready presentations.

Leads and builds Instructure’s decision science function, including hiring, team development, roadmap ownership, experimentation, causal and predictive modeling, executive insights, and data literacy. Partners with product, engineering, marketing, finance, and executives to guide product, pricing, retention, go-to-market, and operational decisions. Establishes analytical standards, supports data infrastructure, and ensures ethical, privacy-conscious use of student data.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages agile sprint planning, release delivery, DevOps metrics, and cross-functional project plans. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, manages team members, and ensures reliable, well-governed data solutions for business intelligence and reporting.

Develops strategic communications, stakeholder engagement plans, executive briefings, dashboards, KPI trackers, and analytical visualizations for global health leadership. Synthesizes complex programmatic, technical, operational, and stakeholder information; analyzes trends, risks, bottlenecks, and performance; and recommends actions. Supports requirements gathering, data quality, reporting standards, process improvement, change management, and engagement tracking across government and external partners.

Leads the design, optimization, and governance of scalable data architectures and pipelines. Ensures data quality, integrity, security, and compliance; mentors junior engineers; conducts audits and validation; and collaborates on data governance. The role requires expertise in SQL, Python, dimensional modeling, Snowflake on Azure, Azure Data Factory, Databricks, ETL, and data warehousing, with preferred experience in Airflow, Kafka, healthcare, data lineage, and slowly changing dimensions.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Collects and analyzes data from project, financial, maintenance, and field systems; builds KPI dashboards and recurring reports; identifies trends, risks, and opportunities; supports budgeting and forecasting; validates data with project and operations teams; and communicates actionable insights to leadership while improving reporting processes.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data platform contributions across engineering, analytics, and BI teams; establish data movement, standardization, governance, security, and compliance practices; evaluate and consolidate tools; manage access, licensing, and spend; and drive architecture standards, documentation, and adoption across the organization.

Leads a data engineering team and oversees the design, development, reliability, security, and scalability of data pipelines, warehouses, platforms, and integrations. Translates business needs into technical solutions, establishes data quality and governance standards, reviews architecture and code, manages projects and resources, resolves infrastructure issues, mentors engineers, and communicates progress and risks to leadership.