Top Remote Analysis Reporting Jobs in Pittsburgh, PA

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Analyze healthcare claims and clinical data to build data models, analytical pipelines, predictive and risk-model inputs, dashboards, scorecards, and reusable analytics assets. Translate ambiguous customer and clinical questions into actionable data plans, manage delivery across stakeholders, present findings to customers, maintain quality standards, mentor junior analysts, and contribute to analytics roadmaps, automation, and scalable methodologies.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

Design, build, and operate scalable data pipelines and integrations for an RCT-driven voter platform. Extend data platform, optimize cost and reliability for election-scale loads, lead cross-system projects, ensure data quality, document systems, and participate in on-call incident response.

The SI Business Analyst will drive integration between business needs and technical delivery, focusing on insurance and healthcare systems. Responsibilities include capturing requirements, performing gap analysis, designing workflows, and leading cross-functional teams to optimize system performance and support digital transformation initiatives.

The Senior Analyst will support the personalization algorithm by conducting analyses, testing features, managing projects, and collaborating with teams to improve food recommendations for customers.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

Lead and mentor a data engineering team building scalable customer-focused data solutions. Hands-on technical ownership, architecture guidance, and delivery of data ingestion, transformation, and reporting. Advance AI-enabled development practices, set technical standards, and foster a collaborative, accountable engineering culture to improve speed, quality, and reliability.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Designs, builds, and supports scalable batch and streaming data pipelines, integration solutions, data models, APIs, and enterprise data platforms. The role focuses on cloud data architecture, data quality, governance, platform performance, and graph capabilities using Neo4j. It partners with stakeholders, analytics, and data science teams to support operational insights, AI, machine learning, fraud detection, and connected-data use cases.