Top Remote Data & Analytics Jobs in Pittsburgh, PA

Owns end-to-end delivery of business intelligence reporting and analytics solutions. Responsibilities include requirements gathering, business process analysis, KPI development, dashboard and report creation, data quality validation, UAT planning and coordination, stakeholder liaison, reporting lifecycle management, and continuous improvement. The role uses Power BI and Microsoft tools to support executive decision-making, optimize reporting processes, improve data integrity, and promote adoption of analytics capabilities across the organization.

Reviews annotated sensor and map data for quality, identifies recurring issues, and recommends solutions. The role prepares reports, maintains annotation policies, develops training documentation, performs data annotation, tests internal tools, reports bugs, and creates visual assets. It also collaborates with stakeholders, partners, annotators, project managers, and engineers while supporting on-road operations and evolving program priorities.

Build and migrate production data engineering and machine learning workloads to Databricks on Azure. Assess on-premises SQL Server and SSIS systems, develop PySpark and Spark SQL pipelines, implement governance with Unity Catalog, and create reusable CI/CD assets. Work directly with Department of Veterans Affairs teams through requirements sessions, workshops, training, and documentation. Depending on focus, build ML workflows or modernize ETL, reporting, semantic models, and Power BI solutions.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.

Builds and maintains scalable data pipelines and reusable datasets in Databricks. Ingests, validates, transforms, and models structured and unstructured data using Python, PySpark, and SQL. Integrates warehouse and cloud analytics systems, supports Tableau and Spotfire reporting, improves reliability and performance, and implements testing, monitoring, documentation, and CI/CD. Collaborates with technical and business stakeholders while providing technical guidance, code reviews, and mentorship.

Develops and maintains Power BI reports, dashboards, semantic models, SQL datasets, and production reporting pipelines. Manages Azure Data Factory pipelines and Databricks notebooks, validates data accuracy, troubleshoots reporting issues, and supports scheduled client deliverables. Collaborates with software engineers, product owners, and account management in an Agile/Scrum environment. Documents BI practices, data definitions, and runbooks while applying dimensional modeling, DAX, Power Query, and AI-assisted development practices.

Partner with Sustainability, Risk, Legal and corporate teams to translate regulatory and reporting needs into scalable data and analytics solutions. Create proofs of concept (basic coding, Power BI), define functional requirements, ensure data quality, and support solution design, integration, and delivery-ready artifacts for sustainability reporting and analytics.

Leads the design, development, governance, and productization of enterprise data models, pipelines, data products, and ontologies. Builds machine-learning-ready datasets, implements security and lineage controls, optimizes Databricks and Delta Lake environments, establishes data-product standards, collaborates with architects and data scientists, and mentors engineering talent. The role also defines product roadmaps, service levels, usage metrics, and continuous-improvement processes for enterprise data assets supporting AI agents, analytics, and applications.

Develop and maintain ETL pipelines, data integration workflows, backend services, and optimized database operations. Build scalable Java and Spring Boot applications, write complex SQL, implement validation and error handling, perform unit testing, troubleshoot pipeline and application issues, and support production deployments. Collaborate with data engineers, developers, QA teams, and business stakeholders while documenting processes and following software development best practices.

Develop and maintain data pipelines using Python, SQL, ETL, and Apache Spark. Extract, transform, validate, and load data from databases, APIs, and files; monitor pipeline performance and quality; support batch and streaming workflows; document processes; and collaborate with analytics and business intelligence teams.

Build and maintain scalable data transformation pipelines, analytics-ready datasets, data warehouses, data marts, and reusable data models using SQL and dbt. Implement data quality testing, validation, monitoring, documentation, and governance while optimizing warehouse performance and integrating multiple data sources. Partner with analysts, product managers, and business stakeholders to support dashboards, KPI reporting, business intelligence, and strategic analytics initiatives.

Owns lead and hotel account data quality for a sales organization. Responsibilities include CRM audits, deduplication, enrichment, lead qualification, routing, SLA development, escalation resolution, data workflow documentation, vendor evaluation, SQL-based validation, and responsible use of AI for quality assurance and anomaly detection.