Data Engineer Jobs in Durham, NC

As a Data Engineer, you'll build and maintain data pipelines for analytics, focusing on Snowflake, while collaborating with teams to ensure data reliability.

As a Senior Backend Engineer, you'll lead data migration projects, design and optimize ETL pipelines, and ensure data quality and consistency across systems.

This role involves designing and managing an Azure-based data platform for marketing analytics, integrating marketing technology, optimizing data pipelines, and ensuring data governance and compliance while implementing DevOps practices.

Lead the Data Curation team, transforming complex biomedical and healthcare data into interoperable models, overseeing data integration and governance, and mentoring engineering staff.

Join the Global Value Engineering Center to consult, develop, and prototype AI-driven solutions using Celonis technology, enhancing business processes.

As a Senior Data Engineer, you'll design and develop models to integrate diverse data sources for analytics and AI applications, ensuring data consistency and quality across domains.

The VP, Data Engineer will lead the development of data solutions and manage data engineering projects while mentoring team members and collaborating across departments to enhance analytics capabilities.

The Principal Data Engineer will lead database architecture and optimization initiatives, modernizing legacy Oracle systems, and driving the data strategy with hands-on implementation and team leadership.

The Data Developer will design a scalable data ecosystem, enhance data models, develop ETL pipelines, ensure data quality, and support analytics.

As a Senior Associate, you will develop and implement IBM MDM solutions, mentor junior team members, and manage data quality frameworks while providing insights from data analysis.

Design, build, and manage data, analytics, and MLOps platforms on Azure. Automate infrastructure and ensure platform reliability while optimizing costs.

Design, develop, and implement data capabilities for Web applications, including database logic, testing, and mentoring junior staff, while optimizing performance and ensuring best practices.

The Data Engineer IV will lead the design and implementation of data solutions using Snowflake, develop ETL pipelines, mentor junior developers, and ensure adherence to data modeling best practices.

As a Data Engineer at Target RWE, you will develop data pipelines, translate business needs into technical solutions, and support cloud infrastructure to enhance operational efficiency.

Develop and maintain ETL pipelines, ensure data integration, collaborate with teams, and optimize data workflows for efficiency.

The Senior Data Engineer will build ETL infrastructure, design cloud applications, perform data analysis, and optimize SQL queries. Responsibilities include developing technical solutions, collaborating on data platforms, and supporting testing phases.

The Senior Data Engineer develops analytics platforms, manages data with SQL and AWS, and creates data models to support business decision-making.

The Principal Software Engineer will design and build scalable data pipelines and analytics for IoT telemetry data, optimizing Spark jobs, utilizing cloud services, and implementing CI/CD in a DevOps Agile environment.

Responsible for designing, building, and maintaining data infrastructure, managing AWS services, and ensuring data reliability for Ecosystem Security.

Responsible for designing and maintaining data infrastructure, building ETL pipelines, managing AWS resources, and collaborating on data services to enhance security.

Lead the design and delivery of large-scale solutions in Generative AI and Big Data, while mentoring teams and driving innovation.

The Sr. Data Engineer will design and optimize scalable data platforms, build data pipelines, and ensure data governance while collaborating with cross-functional teams.

The Staff Engineer - Finance Data Specialist will develop and support a Finance Data Warehouse, collaborating with Finance and Tech teams on data management and analytical solutions.

Design, implement, and manage Google Cloud infrastructure for AI solutions, automate tasks using Python, and ensure application security and performance.

Develop and maintain scalable web applications and services for test automation and chip verification. Collaborate with teams to understand requirements and design user-friendly interfaces.