Top Senior Data & Analytics Jobs in Pittsburgh, PA

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

Leads the architecture, development, and production rollout of an enterprise batch feature store. Designs and tunes PySpark and Impala SQL pipelines using Hive and Oracle, establishes data quality and monitoring standards, manages batch scheduling, and guides developers through technical reviews, releases, and troubleshooting. Coordinates stakeholders, mentors engineers, supports Agile delivery, and ensures CI/CD, testing, change management, and SDLC compliance.

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.

Leads development of tools, automations, and data workflows for engineering systems. Integrates and governs data across Zuken E3, product configurators, MES, PLM, and business platforms; improves component libraries, BOM accuracy, data quality, standardization, and engineering productivity. Partners with engineering, manufacturing, digital, IT, and software vendors to improve workflows, database architecture, process automation, and electrical design operations.

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.

Build and operate scalable data infrastructure, including fault-tolerant pipelines, data discovery services, and data lineage systems. Develop backend services that process petabytes of data for machine learning and autonomy teams. Lead system design, code reviews, and technical contributions while using AWS cloud ETL technologies and distributed systems. Collaborate with stakeholders to improve platform adoption and address data customer needs.

Manage digital analytics supporting eCommerce and Growth Marketing strategy. Translate complex business questions into actionable insights, dashboards, measurement plans, and recommendations. Analyze customer behavior, conversion, revenue, marketing effectiveness, and site performance while ensuring accurate tagging, event tracking, data quality, and analytics implementation. Partner cross-functionally on A/B testing, personalization, digital initiatives, governance, and leadership reporting to identify growth opportunities and improve decision-making.

Designs and maintains operational data infrastructure for smart manufacturing, including pipelines, data warehouses, ETL/ELT processes, time-series data systems, integrations, governance, and trusted datasets. Uses SQL and Python to support reporting, analytics, automation, dashboards, and operational decision-making. Partners across manufacturing and enterprise systems, investigates complex data challenges, evaluates emerging technologies, and supports advanced analytics and digital transformation initiatives.

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.