Top Remote Analysis Reporting Jobs in Pittsburgh, PA

Lead development of the dbt semantic layer and analytics products, own data modeling and metrics, ensure data quality and documentation, support embedded analytics and AI initiatives, and partner with engineering, product, and partners to make data trusted and accessible.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Support a core set of clients by guiding users on Numerator's Insights platform, performing ad-hoc/custom analyses using proprietary consumer panel data, delivering actionable analytic insights and recommendations, and presenting findings across channels including industry forums and written content.

Lead actuarial analyses for value-based care, forecasting Medicare risk and financial performance using large claims and EHR datasets (CCLF, BCDA). Build SQL data structures, IBNR and risk score projections, create executive dashboards, support budgeting, and ensure regulatory compliance under CMS/CMMI programs.

Hands-on technical lead designing and delivering scalable, secure Azure-based BI and analytics solutions. Own end-to-end Power BI architecture, mentor engineers, guide implementations, optimize performance, and advise clients on governance, deployment, and AI-augmented analytics. Drive discovery, backlog priorities, cross-team alignment, reusable assets, and consulting pursuits.

Lead design and governance of enterprise Master Data Management using Stibo/MDM platforms. Define canonical data models, integration patterns (API/event-driven), match & merge and survivorship strategies, stewardship workflows, data quality and lineage, RBAC, and scale multi-domain MDM across Product, Customer, and Supplier domains while aligning with enterprise data governance and cloud platforms.

Design, maintain, and automate GTM business data models, ensure data quality and observability, build BI-as-code pipelines (CI/CD, Git), create visualizations, and partner with Sales, Marketing, Finance, and Product to enable reliable reporting, analytics, and AI capabilities.

Lead data engineer responsible for designing, building, and operating production data pipelines using Python, Airflow, Snowflake, DBT, and AWS. Automate ETL, implement CI/CD, testing and DBT validations, troubleshoot pipelines, and work client-facing to deliver reliable data solutions.

Lead analytics strategy for client accounts: create measurement plans, testing roadmaps, and cross-channel analyses. Use BI tools and SQL to connect data, generate insights, and present clear, actionable recommendations to clients and internal teams.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.