Data Engineer Jobs in Irvine, CA

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

The role involves designing, building, and maintaining ERP data pipelines, ensuring their reliability and supporting data integration initiatives. Responsibilities include troubleshooting, implementing SDLC best practices, and collaborating with stakeholders to optimize data-related outcomes.

The role involves developing scalable data pipelines, automating workflows, optimizing data models, and ensuring data governance while collaborating with various teams.

The Staff Software Engineer will design, develop, and optimize big data systems, collaborating with teams, mentoring junior engineers, and addressing architectural challenges.

The role involves managing data collection and infrastructure for model training, collaborating with scientists for data processing, and extending cloud operations on GCP.