Top Remote Analysis Reporting Jobs in Portland, ME

Design, build, and optimize enterprise ETL/ELT pipelines, cloud data lakes, lakehouse solutions, data models, and semantic layers across AWS and Azure. Ensure data quality, security, performance, reliability, and governance while supporting analytics, reporting, and AI initiatives. Collaborate with product, engineering, IT, and business stakeholders to translate requirements into scalable data solutions, monitor pipeline health, troubleshoot issues, and improve data architecture and practices.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Leads advanced data analysis to guide product and business decisions, develops metrics, dashboards, data products, and AI-enabled reporting systems, and translates findings into strategic recommendations. Partners with data engineers on dimensional data models, data governance, and quality controls. Mentors analysts, aligns roadmaps with business priorities, improves problem framing, and communicates insights effectively to technical and business stakeholders.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Leads enterprise analytics engineering by establishing statistical standards, validation and QA practices, measurement frameworks, reporting standards, governance, reusable data pipelines, automation, and production-grade analytics solutions. Connects Commercial, Medical, Market Access, and other teams to enable scalable, trusted, compliant, and decision-focused analytics. Requires strong technical and cross-functional leadership, analytics infrastructure expertise, and the ability to build enterprise capabilities from ambiguity.

Leads the analytics products team and oversees the development, integrity, maintenance, and delivery of dashboards, reports, models, extracts, and routine data deliverables. Delegates work while remaining hands-on enough to ensure product quality and technology alignment. Partners across revenue cycle business services and applies analytics, project management, change management, business transformation, facilitation, and process improvement practices.

Analyze large healthcare datasets and develop complex SQL queries using Azure Synapse/Databricks. Build Power BI reports, produce monthly reconciliations and ad-hoc analyses in Excel/PowerPoint, support payments to value-based specialists, evaluate and expand value-based programs, automate processes with Power Automate/Power Apps, and communicate findings to senior leadership while spearheading new technologies.

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Develops and maintains enterprise BI reports, dashboards, data models, and visualizations supporting Financial Planning & Analysis. Defines reporting requirements and data standards, analyzes and validates datasets, contributes to data governance, troubleshoots BI issues, and recommends reporting framework enhancements. Collaborates with IT data teams and stakeholders on data integration, documentation, training, and reporting performance improvements.