Top Remote Data & Analytics Jobs in Pittsburgh, PA

Build and optimize Customer 360 data models, ELT pipelines, semantic layers, and identity resolution frameworks in BigQuery. Develop Tableau dashboards for customer acquisition, retention, churn, product adoption, and deposits. Sync behavioral data with marketing and CRM platforms such as Braze, implement data quality and observability controls, and partner with Marketing, Product, and business leaders to turn customer analytics into growth initiatives.

Leads the architecture, development, and production operation of complex data pipelines and platforms. Resolves scalability, data quality, reliability, and architectural challenges; evaluates data technologies; mentors engineers; establishes engineering standards; partners with product, analytics, and operations teams; communicates technical trade-offs; and conducts proofs of concept to guide platform strategy.

Leads consumer, category, market, and growth insights across infant formula and new ventures. Supports qualitative and quantitative research, opportunity sizing, commercialization, pricing, go-to-market strategy, KPI dashboards, syndicated data analysis, campaign evaluation, launch measurement, and executive reporting. Partners cross-functionally with Innovation, Marketing, Sales, Product Development, Finance, research agencies, and data providers to translate intelligence into actionable growth recommendations.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake; architect reusable data assets, governance, and SaaS metrics; build AI-enabled data foundations and LLM workflows; integrate analytics into operational tools and partner cross-functionally to productionize AI-driven use cases.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Build and maintain data pipelines, SQL queries, data models, database structures, and centralized data warehouse capabilities. Clean and validate data, develop reporting datasets and solutions, support KPI tracking and historical analysis, and collaborate with Finance and Revenue Operations. Investigate data gaps, troubleshoot integrations, and independently deliver reliable technical solutions.

Senior Business Insights Analyst partners with executives and cross-functional teams to transform operational, financial, and customer data into actionable insights. The role develops business cases, forecasting tools, KPI frameworks, executive dashboards, performance scorecards, and data governance practices. Responsibilities include strategic and operational analysis, scenario modeling, performance monitoring, executive presentations, and improving enterprise reporting and decision-support capabilities.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.

Build and maintain scalable Snowflake-based ELT/ETL pipelines, production data models, and observability frameworks. Translate business requirements into reliable solutions supporting analytics, BI, and ML. Establish data quality, governance, lineage, security, and compliance practices while optimizing warehouse performance, cost, and data freshness. Collaborate with Analytics, Product, and Engineering teams, contribute to architecture decisions, evaluate Snowflake tooling, and use AI-assisted development tools to accelerate delivery.