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Full time direct hire opportunity with a growing company!

Hybrid- working from the Irvine office three days a week. Only local professionals will be considered.

No sponsorship available.

The Data Engineer is responsible for designing, building, and maintaining data pipelines, data models, and data infrastructure that support analytics, reporting, and operational systems. This role enables the organization to efficiently collect, transform, and deliver high-quality data from ERP systems, manufacturing systems, and other business applications.

Working in a fast-paced, data-driven environment, the Data Engineer collaborates with business intelligence, software engineering, and business teams to ensure data is accurate, accessible, and optimized for decision-making and operational efficiency.

Responsibilities:

• Design, develop, and maintain scalable data pipelines to extract, transform, and load (ETL/ELT) data from multiple sources
• Build and optimize data models to support analytics, reporting, and downstream applications
• Integrate data from ERP, MES, and other enterprise systems into centralized data platforms
• Ensure data quality, integrity, and consistency across data pipelines and storage systems
• Monitor and troubleshoot data workflows, resolving performance and reliability issues
• Optimize query performance and data processing efficiency
• Collaborate with BI engineers and analysts to support reporting and analytics requirements
• Develop and maintain data documentation, including data definitions, lineage, and transformations
• Support deployment and maintenance of data solutions in production environments
• Work with software engineering teams to support data integration and application data needs
• Automate data workflows and reduce manual data handling processes
• Update and track work items using Atlassian or similar project management tools
• Continuously evaluate and implement improvements to data architecture and tooling

We are looking for:

• Bachelor’s degree in computer science, engineering, data science, or related field (or equivalent experience)
• 4–6 years of experience in data engineering,
• Strong proficiency in SQL and experience with relational databases such as SQL Server
• Experience with ERP or manufacturing data environments
• Experience with Azure Cloud data platforms or modern data stacks
• Experience building ETL/ELT pipelines and data workflows
• Proficiency in programming languages such as Python or similar
• Understanding of data modeling concepts (dimensional modeling, normalization)
• Experience working with large datasets and optimizing performance
• Familiarity with data warehousing concepts and architectures
• Experience with version control systems such as Git
• Experience with BI tools such as Power BI or similar
• Experience working in Agile/Scrum environments
• Excellent communication skills