Top Remote Analysis Reporting Jobs in Greensboro, NC

Drives data collection, analysis, KPI reporting, dashboard development, forecasting, and executive presentations. Builds standardized reporting processes, improves data quality, investigates metric fluctuations, and translates business requirements into actionable insights. Collaborates with cross-functional teams, leadership, vendors, and partners to prioritize information needs, maintain data integrity, automate reporting, and communicate findings effectively.

The role involves designing and developing customizations for IBM Infosphere MDM, focusing on data management architecture and multi-domain solutions.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Leads the design, optimization, and governance of scalable data architectures and pipelines. Ensures data quality, integrity, security, and compliance; mentors junior engineers; conducts audits and validation; and collaborates on data governance. The role requires expertise in SQL, Python, dimensional modeling, Snowflake on Azure, Azure Data Factory, Databricks, ETL, and data warehousing, with preferred experience in Airflow, Kafka, healthcare, data lineage, and slowly changing dimensions.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

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.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Collects and analyzes data from project, financial, maintenance, and field systems; builds KPI dashboards and recurring reports; identifies trends, risks, and opportunities; supports budgeting and forecasting; validates data with project and operations teams; and communicates actionable insights to leadership while improving reporting processes.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data platform contributions across engineering, analytics, and BI teams; establish data movement, standardization, governance, security, and compliance practices; evaluate and consolidate tools; manage access, licensing, and spend; and drive architecture standards, documentation, and adoption across the organization.

Leads a data engineering team and oversees the design, development, reliability, security, and scalability of data pipelines, warehouses, platforms, and integrations. Translates business needs into technical solutions, establishes data quality and governance standards, reviews architecture and code, manages projects and resources, resolves infrastructure issues, mentors engineers, and communicates progress and risks to leadership.