Top Remote Data Engineer Jobs in Pittsburgh, PA

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

As a Data Engineer, you'll manage data access, support development and analytics teams, implement automated processes, engineer data pipelines, and ensure data accuracy.

Lead the implementation of AML detection pipelines using Palantir Foundry. Train team members in technical skills and oversee data architecture and maintenance.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Design and deploy data processing pipelines, analyze data to extract insights, and develop software systems for data management and privacy.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

The Data Architect designs data flows, defines standards, ensures data quality, and collaborates on data strategies while integrating advanced technologies.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

The Data Quality Engineer ensures the accuracy and reliability of healthcare data pipelines, drives QA automation, and collaborates with cross-functional teams to resolve data integrity issues.

The Senior Data Engineer will focus on ingesting and curating satellite imagery and geospatial data, building data pipelines, and mentoring junior engineers, while ensuring performance and scalability.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

The Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

As a Senior Data Engineer, you will build data infrastructure, develop CI/CD pipelines, and create entity resolution systems, focusing on large-scale data processing and analytics.

The Data Visualization Engineer will create data storytelling products, enhancing user experiences with intuitive data representations and collaborating closely with stakeholders on visual applications.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

Lead the architecture and development of scalable data pipelines, mentor team members, and align data engineering practices with business objectives in a complex technical environment.

The Senior Data Engineer will develop scalable data pipelines, maintain production datasets, collaborate with teams, and optimize data platform infrastructure.

The Senior Data Engineer develops and maintains data pipelines, collaborates on scalable data solutions, and ensures data security via cloud services.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.

Analyze and develop data solutions, lead projects, translate business requirements, provide support for ETL processes, and mentor junior team members.