Top Remote Data & Analytics Jobs in Pittsburgh, PA

Collect, clean, validate, and analyze operational data from multiple systems to support customer reporting and performance monitoring. Process SQL-based uploads, maintain accurate datasets, identify trends and anomalies, document reporting procedures, and create standardized workflows, dashboards, and tools. The role also supports process improvement and automation initiatives while collaborating with cross-functional teams and traveling to customer sites.

Design and support ETL, data migration, transformation, import, export, and validation workflows for moving legacy EHR data into athenahealth systems. Build Python and SQL utilities, define source-to-target mappings, support HL7 and FHIR interoperability, validate EHI exports, investigate data quality issues, document processes, and collaborate with product, implementation, operations, sales, and engineering teams in a remote environment.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Scout collegiate basketball games from stadiums using proprietary software to quickly and accurately record live game information. Responsibilities include identifying basketball concepts and player details throughout games, maintaining reliable communication and punctuality, and traveling to assigned venues as needed. The primarily part-time, pay-per-game role runs from October 15, 2025, through April 15, 2026, with opportunities for incentives and future advancement.

Lead study design, survey development, questionnaire quality, data analysis, and client-ready reporting for financial services research. Interpret findings with client teams, translate results into actionable business insights, apply analytical methods, and ensure accuracy, clarity, timeliness, and integrity across multiple projects.

Designs and maintains healthcare data pipelines, ETL workflows, databases, data models, and analytical frameworks. Analyzes claims and payer data to identify trends and insights, while ensuring data quality and integrity. Creates reports, dashboards, and visualizations for nontechnical stakeholders and collaborates with healthcare policy experts, analysts, and other stakeholders to translate requirements into data solutions. The role also improves data infrastructure and analytics capabilities.

Produces publishable maps, graphs, and visualizations of conflict patterns and analysis outputs. Transforms complex datasets into compelling visual stories, develops visualization guidelines, researches new methods and software, and supports visual brand development. Collaborates with regional experts, media, partners, and external stakeholders, responds to journalist inquiries, ensures data accuracy, and contributes to outreach, reporting, coordination, and communications activities.

Analyze and design enterprise healthcare data solutions using Snowflake and advanced SQL. Perform data profiling, reconciliation, anomaly detection, source-to-target validation, and quality testing across claims, membership, provider, and health plan data. Support data architecture, dimensional modeling, governance, metadata, lineage, cataloging, and MDM initiatives. Prepare data for AI and advanced analytics, translate business requirements into solutions, resolve data issues with stakeholders, and communicate actionable insights while following security and HIPAA requirements.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, and SQL. Supports SQL Server, SSIS, SSRS, and data warehousing environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, enables reporting and AI/ML workloads, and partners with business and IT teams to deliver technical data solutions.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, SQL, and Delta Lake. Supports SQL Server, SSIS, and SSRS environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, applies data warehousing practices, and partners with business users, analysts, and IT teams to deliver reporting, analytics, and AI/ML solutions.