Top Senior Analysis Reporting Jobs in Hartford, CT

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

The Staff Data Analyst will build Boulevard's product data foundation, create data-driven recommendations, develop dashboards, conduct deep analyses, and foster a data-driven culture within the organization.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

Lead design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

Lead customer engagements to architect, implement, and optimize large-scale Spark and Databricks workloads. Troubleshoot and tune distributed PySpark and DBSQL jobs, design PoCs/workshops, advocate technical solutions, mentor junior engineers, and collaborate cross-functionally to improve platform features and cost-efficiency.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.