Top Analysis Reporting Jobs in Hartford, CT

Leads enterprise analytical modeling and semantic architecture, establishes standards for testing, documentation, governance, lineage, observability, and access, and develops reusable governed data products. Partners across Product, Engineering, Finance, Clinical, Research, Marketing, and AI teams; guides architecture reviews, data quality ownership, semantic layer design, and governance adoption. Mentors engineers and drives modernization of analytical environments.

Leads Versapay’s enterprise data strategy, architecture, governance, quality, accessibility, and commercialization. The role unifies transactional and analytical data, establishes semantic models and data catalogs, enables secure AI and agentic capabilities, develops external data products, manages data platform costs, and leads teams across data engineering, analytics, BI, and platform operations. The Senior Director partners with executive, product, engineering, commercial, finance, legal, and compliance stakeholders.

Supports Indonesian and broader Asian survey operations by monitoring data quality, managing quality-control staff, correcting survey issues, analyzing collection progress, and developing data-quality tools. Coordinates field operations, training, stakeholder engagement, translations, and backcheck processes. Provides insights on coffee and cacao sustainability data to country teams and supply-chain stakeholders. The role is fully remote from Indonesia with travel to regional agricultural areas.

Partner with Ads sales to provide data-driven prospecting, reporting, and strategic recommendations. Build SQL queries and dashboards, produce monthly/quarterly client narratives, run incrementality/A-B tests, and present insights to brands. Support new business pitches, automate reporting workflows, and collaborate with Sales, Ad Ops, and Product on ad performance and product testing.

Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.

Build and maintain a global knowledge base of electronic-resource metadata. Responsibilities include analyzing publisher data, creating and maintaining collections, establishing data feeds, researching missing metadata, documenting transformation processes, resolving data issues through root-cause analysis, coordinating with vendors, and managing workload priorities. The role requires advanced Excel skills, attention to data quality, strong communication, and familiarity with metadata standards.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Analyzes web, customer, and campaign data to generate actionable digital marketing insights. Builds dashboards and presentations using Adobe Analytics, Power BI, or Tableau; evaluates site performance, media monetization, A/B tests, and web projects; supports tagging, reporting validation, and vendor implementations. The role partners with stakeholders and Agile teams, manages analytics priorities, and communicates findings to guide marketing strategy and business decisions.

Leads enterprise data architecture strategy, modernization, and multi-year platform roadmaps. Defines standards for data models, ingestion, transformation, orchestration, quality, governance, observability, and consumption across batch and streaming environments. Provides technical leadership to data engineering and analytics teams, oversees scalable data solutions, mentors technical leaders, and partners with business, engineering, security, and data science stakeholders. Evaluates technologies, guides vendor selection, enables data products, and explores GenAI applications.

Leads the design, automation, optimization, and maintenance of scalable data pipelines using Airflow, dbt, Python, SQL, and Google Cloud technologies. Manages dbt models, develops reusable architecture patterns, monitors pipeline performance, supports CI/CD and testing, and ensures data security and governance. The role also provides technical leadership, mentors engineers, collaborates cross-functionally, documents implementations, and drives continuous improvement across data engineering practices.