Top Remote Data & Analytics Jobs in Pittsburgh, PA

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Develop and run SAS programs to validate and clean surveillance and research data, create codebooks and data plans, perform geospatial and molecular HIV analyses in R, collaborate on novel code and reporting, and support dissemination to federal and external partners while ensuring data quality and documentation.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Analyze marketing channel performance (Paid Media, CRM, Email, engagement), prepare recurring reports, consolidate data into actionable summaries, perform QA on reports/datasets, support client recommendations and optimizations, collaborate with cross-functional teams, and use AI tools responsibly to improve efficiency.

Analyze customer and caregiver data to identify workflow improvements, build dashboards and visualizations, support Customer Success with QBRs and presentations, translate findings into actionable recommendations, and create scalable data processes while advising Product and Engineering.

Part-time contractor responsible for database maintenance, advanced Excel data manipulation and reporting, CRM management, KPI development, data visualization, and consulting with executives to improve processes and present findings.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Lead customer engagements to architect, implement, and optimize large-scale Spark and Databricks workloads. Troubleshoot and tune distributed PySpark and DBSQL jobs, design PoCs/workshops, advocate technical solutions, mentor junior engineers, and collaborate cross-functionally to improve platform features and cost-efficiency.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.