Top Analysis Reporting Jobs in Hartford, CT

The Data Governance Specialist develops and enforces data governance, quality, privacy, risk, and compliance standards across organizational data assets. Responsibilities include managing metadata, data dictionaries, lineage, classification, retention, PII controls, DPIAs, risk assessments, audits, dashboards, and data-quality remediation. The role partners with engineering, security, legal, and business teams, provides stakeholder training, investigates data integrity issues, supports incident escalation, and automates governance processes through scripting.

Lead the data engineering strategy and architecture for distributed pharmaceutical data systems. Design and scale pipelines, APIs, and data platforms while ensuring reliability, governance, quality, and PII/PHI protection. Drive technical decisions, improve developer efficiency, deliver business impact, influence cross-functional roadmaps, mentor engineers, communicate with executives, and promote organizational adoption of new technologies and processes.

Administers Oracle databases across development, test, staging, and production environments. Performs monitoring, maintenance, backups, recovery, patching, tuning, schema updates, indexing, troubleshooting, access control, encryption, auditing, and compliance remediation. Supports migrations, releases, environment synchronization, documentation, and collaboration with development and cybersecurity teams. Requires an active Top Secret clearance, database administration experience, relevant certifications, and strong Oracle, SQL, PL/SQL, and DoD security knowledge.

Design and own a unified data model for an AI-driven pipeline risk platform. Responsibilities include lakehouse and medallion architecture, geospatial modeling, entity resolution, ingestion patterns, governance, lineage, data quality, access controls, and traceability. Partner with data engineers, application engineers, and data scientists to implement schemas, pipelines, serving layers, and optimization strategies while maintaining clear architecture documentation.

Supports cross-functional manufacturing, finance, engineering, IT, and operations initiatives through data consolidation, business analysis, KPI reporting, requirements gathering, and cost-benefit analysis. The role develops recommendations, project status reports, presentations, and post-project audits while helping support strategic decisions and operating effectiveness. This position is remote within specified states and requires up to 25% travel.

Leads the data engineering organization and enterprise Databricks Lakehouse on AWS. Owns team development, platform strategy, delivery, reliability, governance, budget, vendors, architecture standards, and regulatory compliance. Partners with executives on data transformation, MDM, ERP migration, analytics, and AI enablement. Requires extensive data engineering leadership, Databricks and AWS expertise, regulated-environment experience, and proven budget and vendor management.

Manage Oracle and PostgreSQL databases across on-premises and AWS environments, including upgrades, migrations, performance tuning, security, and backup recovery. Design and maintain ETL pipelines using Talend, SQL, Power Automate, and related tools. Perform data profiling, quality analysis, governance, and cloud migration activities. Create technical architecture and lineage documentation while supporting regulated, audit-ready data platforms and integrations.

Lead the architecture, design, development, troubleshooting, and optimization of Snowflake data solutions for higher education clients. Conduct discovery and design workshops, assess existing environments, create enterprise data models and future-state architectures, develop ETL/ELT pipelines, implement security and data-quality controls, and optimize performance and costs. Serve as a client-facing technical advisor, translate business requirements into scalable solutions, lead technical workstreams, support business development, mentor teams, and travel periodically.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.

Own measurement strategies for large omnichannel brands, including test design, marketing mix modeling, incrementality analysis, attribution interpretation, and budget recommendations. Translate complex findings into actionable guidance for executives and marketing teams, support prospect conversations, identify customer and product gaps, and collaborate with Product, Data Science, and Customer Success. The role requires strong paid media expertise, omnichannel fluency, statistical measurement literacy, and the ability to communicate uncertainty and recommendations clearly.