Top Data Engineer Jobs in Pittsburgh, PA

The Senior Data Engineer will design and implement ETL processes in a cloud environment, develop monitoring solutions, document datasets, and collaborate with the Data Science team. This role requires building ETL processes and a strong understanding of data modeling.

As the Director of Data Science & AI, you will lead a team to develop AI and ML solutions that align with the business strategy. Responsibilities include overseeing the ML workflow, collaborating with Product and Engineering, and managing a high-performance team to drive customer-centric analysis and strategic initiatives.

The Data Processor will manage data entry tasks, verify information within computer applications, and generate reports using MS Excel. Collaboration with team members to meet tax deadlines and maintain audit reports is also expected.

Conduct research to inform workforce policy on technology, supply chain, and infrastructure strategies. Collaborate with CMU researchers and mentor students while engaging with the scientific community to address national security and economic challenges.

The Data Steward will oversee and manage government-managed and commercial parts data, ensuring its accuracy, consistency, and accessibility. Responsibilities include data quality assessments, developing data standards, collaborating with stakeholders, and utilizing SQL for data analysis. The role demands excellent communication skills and attention to detail.

As a Data Entry Specialist at Carvana, you will handle the registration process for customer vehicles, ensuring accuracy of documents and maintaining detailed records. You will be required to interact with local DMV and government licensing departments, manage multiple tasks, and support customers through the administrative process of vehicle ownership transition.

In this role, a Staff Data Analyst will work with engineering teams to enhance the Aurora Driver through data analytics, developing metrics and dashboards, mentoring in the data space, and collaborating on various Data Science projects to improve performance across subsystems.