Top Senior Data & Analytics Jobs in Pittsburgh, PA

Leads enterprise data architecture, SQL Server administration, data warehouse design, ETL/ELT pipelines, Azure data platforms, data governance, master data management, and business intelligence strategy. Partners with business and IT stakeholders to deliver scalable analytics solutions across financial, HR, CRM, operational, and practice management systems. Provides technical leadership, vendor coordination, architecture documentation, and mentorship.

Owns segmentation, forecasting, reporting, and analytics for consumer banking acquisition and direct mail marketing campaigns. Builds campaign files, dashboards, visualizations, and marketing spend forecasts using large datasets and analytical tools. Partners with stakeholders to communicate insights, validate solutions, identify trends, and support strategic decisions. Reviews junior analysts’ work, provides mentorship, and coordinates team activities while ensuring accurate documentation and testing.

Builds and architects complex ETL pipelines and data integrations for an enterprise data lakehouse. Responsibilities include designing workflows, monitoring data movement across cloud and on-premise systems, improving data quality, implementing master data management, documenting lineage, troubleshooting integrations, and standardizing data processes. The role collaborates with business units, analysts, visualization engineers, IT, and data scientists to enable new data sources and resolve complex technical issues.

Designs and maintains CORE’s enterprise analytics data platform, including dimensional data warehouses, ETL/ELT pipelines, semantic models, and governed datasets. Integrates clinical, financial, workforce, donor, and operational data while ensuring platform security, reliability, performance, quality, lineage, documentation, and monitoring. Supports Power BI, advanced analytics, and responsible AI initiatives, collaborates with technical and business stakeholders, and translates requirements into sustainable production solutions.

Owns the enterprise Data Lakehouse platform, including operations, configuration, integrations, monitoring, validation, issue resolution, vendor management, releases, documentation, security controls, and lifecycle planning. Translates business and data requirements into platform solutions, coordinates cross-functional technology teams, and ensures reliable support for business intelligence, reporting, analytics, and AI use cases. Provides technical leadership and guidance without direct personnel-management responsibility.

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.

Designs, develops, and executes complex Informatica ETL workflows and enterprise data integration pipelines. Optimizes SQL and database performance, prepares data mappings and technical documentation, troubleshoots pipeline failures, reviews code and testing plans, and guides engineering peers. The role supports reliable data movement, data quality, security compliance, release management, and enterprise banking analytics initiatives.

Designs, develops, and governs enterprise ontologies and semantic models for knowledge graphs and AI applications. Translates scientific and business concepts into scalable knowledge structures, mappings, taxonomies, and controlled vocabularies. Establishes ontology quality, lifecycle, provenance, versioning, and change-management practices. Partners with scientific, product, data, AI, and engineering stakeholders to improve semantic search, content discovery, RAG, knowledge grounding, recommendations, and data interoperability.

Leads a small team responsible for enterprise data engineering, data warehousing, database administration, integrations, SharePoint, Nintex automation, Power BI enablement, governance, security, and operational reliability. The role owns Microsoft Fabric and EDW architecture, builds and supports ETL/ELT pipelines, manages platform roadmaps and vendors, applies AI-enabled automation, and partners with IT and business stakeholders to deliver trusted, secure, governed data services.

Manage macroeconomic and financial datasets for economic forecasting, regulatory stress testing, and reserve estimation. Responsibilities include data collection, updates, validation, revision review, documentation, model-development support, vendor collaboration, and responding to ad hoc requests. The role requires coordinating with modelers and bank teams while delivering accurate results on schedule. Strong quantitative, communication, organizational, and analytical skills are essential; R or Python programming is preferred.