Top Remote Data & Analytics Jobs in Pittsburgh, PA

Build, maintain, and support production data pipelines and platform capabilities using Snowflake, dbt, Airflow or Cloud Composer, APIs, files, and cloud services. Responsibilities include ETL/ELT development, data modeling, testing, deployment, monitoring, troubleshooting, optimization, documentation, and data quality. The role partners with analytics, data science, finance, risk, marketing, product, and engineering teams, while supporting reliable, scalable, and cost-effective data systems and emerging AI data workflows.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Own analytics implementation and data integration for B2B ecommerce clients. Build GA4 and Google Tag Manager implementations, marketing pixels, conversion APIs, product feeds, BigQuery data models, and Looker Studio dashboards. Reconcile analytics, advertising, ecommerce, and ERP data; audit tracking issues; support CRO and experimentation; and translate findings into actionable recommendations for clients and leadership. Collaborate with developers, marketers, merchandisers, and other stakeholders while maintaining accurate, privacy-compliant measurement.

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Design and optimize enterprise data architectures and pipelines using SQL, Spark/PySpark, Python, Apache Iceberg, AWS, ClickHouse, and PostgreSQL. Build greenfield application and data solutions, optimize databases and Spark jobs, integrate data virtualization and governance tools, and support CI/CD and infrastructure-as-code practices. Experience with financial services workloads is valued, while telecommunications knowledge is preferred but not required.

Analyzes, validates, and maintains Army MEDCOM facilities and real property data; supports dashboards, reporting, data integration, quality assurance, process improvement, documentation, training, and stakeholder deliverables. The role identifies data discrepancies, develops recommendations, provides technical support, and assists with Medical Readiness and Facility Investment Plan requirements. Periodic travel to project sites, meetings, training, and data collection locations may be required.

The description combines recruitment management, event planning, business development consulting, and iOS application development. Responsibilities include developing recruitment strategies, training recruiters, maintaining candidate databases, coordinating events, managing vendors and client relationships, developing sales pipelines, and designing, testing, updating, and maintaining iOS applications.

Own and operate the analytics platform: design and deploy the semantic/metrics layer, administer the data catalog and self-service BI tooling, optimize Amazon Redshift performance, ensure platform reliability/observability, manage security and access policies, and lead tool migrations and vendor evaluations to enable self-service analytics at scale.

Analyze complex construction and design project data, develop datasets, pipelines, reports, dashboards, and predictive or prescriptive models. Partner with business, IT, and data governance teams to address reporting needs, improve processes, establish metrics, manage data access, support governance, and generate actionable insights for capital portfolio decisions.