Top Hybrid Data & Analytics Jobs in Detroit, MI

As a Senior Manager in Data and Analytics Engineering at PwC, you'll design data architecture strategies for healthcare, mentor teams, influence stakeholders, and enhance healthcare operations through data solutions.

The role involves leading finance big data assets governance, managing the data stewardship team, defining data quality rules, and collaborating with various stakeholders for analytics and AI governance.

The Category Data Analyst supports sourcing activities through data analysis, market intelligence, and reporting, enabling informed decision-making and supplier management.

As a Quality Analytics Analyst, you will develop capabilities for early detection of quality issues, lead resolutions, analyze data to identify trends, and maintain performance tracking dashboards.

As a Senior Data Engineer at SpotOn, you'll architect and maintain scalable data systems, design data pipelines and ETL processes, optimize SQL queries, and mentor junior engineers, all while collaborating with cross-functional teams.

The Infor Syteline Business Analyst/Developer analyzes business requirements, customizes modules, integrates systems, provides support, and trains users in the ERP system.

The role involves leading a team to grow and retain business in online communities and panels, managing recruitment, engagement, and data quality while overseeing the operational excellence and compliance within global markets.

The Manager focuses on OneStream, leading implementations and technical support for clients, gathering requirements, and ensuring effective solutions. Collaboration with teams and client training are key responsibilities.

This role involves leading the Data & AI team, building modern data platforms using Microsoft technologies, overseeing project delivery, and mentoring team members while engaging with clients.

The Senior Data Architect will design and implement data architecture strategies, integrating Oracle EBS with cloud services, overseeing data governance, and collaborating with cross-functional teams to optimize data workflows.