Top Data Management Jobs in Pittsburgh, PA

The Manager, Master Data Management will lead MDM strategies and teams, ensuring data accuracy and governance in an enterprise context.

The Data Manager will support partners by addressing data needs, managing issues, and implementing best practices for effective data use in civic engagement campaigns.

Lead and manage a team of data engineers, oversee data warehouses and pipelines, ensure scalable data architecture, and foster partnerships with data analysts and scientists.

Responsible for leading a team in advanced data analytics, creating automated reports, and providing insights to senior leaders, while ensuring data accuracy and documentation.

The Data Analytics Manager for Travel optimizes corporate travel operations by analyzing data, improving compliance, forecasting budgets, and developing performance reports with actionable insights.

Manage data governance and Master Data Management, ensuring data quality and oversight. Collaborate with stakeholders and IT on data architecture and strategy.

Lead a team to develop data technology solutions within an Agile framework, managing data platforms and ensuring delivery aligns with business priorities.

The Senior Data Manager is responsible for acquiring, cleaning, and managing datasets, developing data architectures, and ensuring data accessibility for business analysis and reporting.

Lead a data science team to enhance Netflix's streaming product through analytics and experimentation, partnering with engineering.

Lead a data science team to drive consumer acquisition strategies and improve Netflix's signup processes through analytics, experimentation, and machine learning.

The Manager, Data Analysis oversees centralized monitoring for clinical trials, ensuring effective RBQM systems, data analysis, and reporting while collaborating with cross-functional teams.

Lead clinical data management for studies, oversee CROs, ensure data quality, coordinate data review, and assist in clinical system implementations.

Lead a team of Data Scientists, Analytics Engineers, and Data Engineers to drive messaging strategies through analytics and data science, ensuring collaboration across various business domains.

The Senior Data Manager will design, configure, and launch clinical trials on Citrus while managing data quality and collaborating with product teams and stakeholders.

As a Data Manager, you will oversee data management for clinical trials, ensuring quality outcomes, designing data capture tools, and collaborating on product development.

This role involves leading data projects, managing analytics, delivering insights, and mentoring team members while collaborating on data strategies for clients.

Manage marketing data systems, track pipeline and revenue analytics, ensure data quality, and provide proactive insights. Collaborate with cross-functional teams to align on metrics and reporting.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

As a Data Analytics Manager, you will lead a team to analyze data, drive strategic insights, manage projects, and optimize mobile app performance for top brands.

Lead and mentor a Data Engineering team, manage data operations, ensure compliance with HIPAA, and design scalable ETL pipelines while collaborating across departments.

Lead AI and data initiatives to enhance marketing capabilities and drive growth. Collaborate across teams to optimize data usage for better performance and decision-making.

The Senior Manager, Data Science & Analytics will lead a team to drive analytics and experimentation strategies for Yahoo Mail's growth and monetization, engaging with product, finance, and marketing to transform data insights into actionable strategies for success.

The Data Conversion Manager oversees new customer onboarding, facilitating data migrations to the Encompass Cloud Platform, ensuring quality and accuracy in data transfers across systems.

Manage a team of analysts while analyzing data, reporting, and enabling AI/ML model deployment. Provide insights and automate processes.

Manage a team of data scientists to develop fraud detection models, mentor staff, and collaborate with leadership on solutions and product development.