Top Remote Data & Analytics Jobs in Pittsburgh, PA

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The Data Engineer will design and maintain scalable data pipelines, automate workflows, and enhance data governance while collaborating with cross-functional teams.

The Data Migration Specialist will ensure successful data transitions from legacy systems, engage in ETL processes, and provide customer support throughout the migration journey.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Analyze, trace, reconcile, and migrate insurance policy data from legacy systems into a modern policy platform. Build source-to-target mappings and ETL transformations, perform data cleansing and validation, write complex SQL, use cloud databases (AWS RDS/S3), and collaborate with stakeholders using GitHub and Agile tools. Heavy daily use of AI tooling; mentorship provided throughout migration lifecycle.

Design, modernize, and optimize hybrid cloud and legacy relational databases (Informix, DB2, MySQL, Oracle, PostgreSQL). Collaborate with engineers and security teams to implement migrations, performance tuning, data modeling, SQL/PLSQL development, automation, and DevSecOps practices to support cloud adoption and mission-critical operations.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Lead development and ownership of end-to-end data pipelines and platform tools. Build and optimize ingestion, transform data with dbt and Jinja, implement monitoring/alerting, manage deployments and CI/CD, and create self-service analytics applications and internal tooling.