Top Analysis Reporting Jobs in Hartford, CT

The Analytics Engineer develops end-to-end analytics solutions and business applications to streamline Operations and enable digital transformation. Responsibilities include communicating analytics to nontechnical stakeholders, supporting cross-functional supply chain, manufacturing, and quality projects, developing business processes, selecting methodologies and technologies, and improving operational efficiency. The role is fully remote and may involve AI technologies, full-stack development, and optimization modeling.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Designs, builds, and maintains scalable data pipelines, data models, and platform infrastructure supporting enterprise reporting, analytics, and AI-driven decisions. Responsibilities include ingesting SaaS application data, developing medallion architecture layers and dbt transformations, implementing data quality monitoring, enforcing governance and access controls, and delivering reusable semantic data assets. The role collaborates with analytics, BI, and business teams, participates in Agile delivery, evaluates modern data-stack tools, and promotes engineering excellence through testing, documentation, and code reviews.

Design, build, and operate scalable cloud-native data pipelines and data lake/fabric architectures for Revenue Cycle Management. Implement ETL/ELT, integrate structured and unstructured sources and APIs, ensure data quality, lineage, and governance, and support AI/ML and analytics workloads with CI/CD and DevOps practices.

Lead and own end-to-end delivery of enterprise Data & AI programs, define data strategy and architecture (lakehouse/warehouse), drive modernization, governance, data quality, metadata/lineage, and AI adoption. Manage client relationships, account growth, program budgets, delivery teams, and stakeholder communications to ensure on-time, on-budget outcomes.

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.

The Analytics Lead will guide data-driven decision-making, develop measurement frameworks, forecast revenue, and mentor an analytics team, ensuring effective communication of insights.

Owns the design, governance, and operational oversight of mortgage document-to-data processes. Performs data validation, reconciliation, exception management, quality control, and anomaly identification across acquisitions, servicing transfers, due diligence, collateral management, and asset management. Collaborates with stakeholders, technology teams, vendors, custodians, and servicing partners to resolve data issues, improve processes, and enhance loan data integrity.

Design, build, and maintain scalable data pipelines, data models, and analytics solutions using Microsoft Fabric and Azure. Develop Lakehouse and Warehouse architectures, Fabric Notebooks with PySpark and Spark SQL, ETL/ELT workflows, and Power BI semantic models. Optimize performance, ensure data quality, security, governance, and regulatory compliance, and collaborate with analysts, data scientists, and business stakeholders to support business intelligence and advanced analytics.

Clean and reconcile employee master data and historical leave records from multiple sources. Define standardized HR data structures, establish validation and access controls, and automate leave request, approval, and balance tracking workflows using Google Workspace or a suitable alternative. Document maintenance processes and support potential expansion across international branches. The contractor will independently manage the fixed-scope project, propose an RFQ, and provide timeline, hours, costs, assumptions, and deliverables.

Leads enterprise Snowflake architecture, administration, governance, security, performance, and cost optimization across AWS and Azure. Manages Snowflake administrators and data engineers, serves as Product Owner, and leads delivery for federal and public-sector clients. Responsibilities include stakeholder management, technical escalations, data integration, agile backlog prioritization, risk and SOW management, and executive engagement.