Top Data Management Jobs in Pittsburgh, PA

Lead and manage Managed Data & Analytics engagements, build modern data ecosystems, convert insights into strategic opportunities, mentor teams, ensure project delivery, uphold standards, and drive cloud-scale data solutions.

Lead development and execution of data governance strategies, manage client accounts and engagement workstreams, mentor and supervise teams, ensure quality and compliance with firm standards, analyze data to inform business decisions, and identify process improvements to enhance data management and analytics solutions.

Lead development and execution of data-driven strategies, manage project timelines and team performance, analyze complex datasets to produce actionable insights, implement data governance and modern cloud data architectures, and coach team members while ensuring quality, ethics, and continuous improvement across client engagements.

Lead design and delivery of data engineering solutions for clients: build and maintain data pipelines and architectures, apply AWS/Redshift and ETL tooling, implement BI visualizations, coach teams, engage stakeholders, apply systems thinking, validate outcomes, and manage managed-services SLAs to optimize business performance.

Lead design and implementation of data architecture, data models, ETL/ELT pipelines, and data platform solutions. Manage data warehouses/lakes, enforce governance and security, troubleshoot pipelines, coach team members, engage stakeholders to translate requirements, and recommend cloud and tooling improvements to enable data-driven decisions.

Lead data engineering projects and teams to design, build, and maintain scalable ETL/ELT pipelines, cloud analytics platforms, and BI/reporting solutions. Mentor staff, manage client relationships, ensure project delivery, and promote technology adoption and process improvement to drive data-driven business decisions.

Lead design and implementation of data architecture, pipelines, and cloud-based solutions. Manage large projects, advise clients strategically, ensure data governance and security compliance, document data models/flows, and build high-performing inclusive teams while coaching and driving operational excellence.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead development and execution of data governance strategies, supervise and mentor teams, manage client accounts and deliverables, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements to data management processes.

Lead development and execution of data-driven strategies, manage and mentor a data analytics team, oversee project planning and delivery, analyze complex datasets to produce actionable insights, implement cloud data architectures, and support data governance and continuous improvement.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

The Senior Manager will lead data analytics and pricing strategies in CAD, improving data processes, analytical workflows, and decision-making capabilities while managing a high-performing analytics team and collaborating with various stakeholders.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead design and build of a cloud-based data platform; manage and mentor data engineering staff; define engineering standards, data governance, and access controls; partner with stakeholders to deliver scalable, reliable data pipelines and platform services for analytics and AI.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Design, implement, and operationalize an enterprise data governance framework. Lead governance councils, define stewardship and metadata practices, ensure regulatory compliance, integrate AI governance, monitor KPIs, and drive adoption across business, technology, risk, and compliance.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.