Data Engineer: Scalable Warehouses & Real-Time Pipelines

HappyGlobal Service; California; On-site; USD 120,000 - 180,000; Full time

Job summary

HappyGlobal Service is seeking an experienced Data Engineer to design, develop, and maintain scalable data warehouse solutions and processing pipelines. You will collaborate with cross-functional teams to deliver reliable data assets that drive data-driven decisions.

The ideal candidate combines strong technical skills with business understanding and can translate complex requirements into scalable data architectures. Strong knowledge of big data tech and modern data modeling is required.

Qualifications

• Bachelor's degree in a related field or equivalent professional experience.
• Hands-on data warehouse modeling and development experience.
• Experience with batch and real-time data processing.
• Experience with large-scale, high-throughput data systems preferred.
• Proficiency in Hadoop/Spark/Iceberg/Flink; Java/Scala/Python proficiency.

Responsibilities

• Design, develop, and maintain offline data warehouses and pipelines.
• Establish data modeling standards and data quality practices.
• Optimize architecture for scalability, performance, and maintainability.
• Collaborate with cross-functional teams to meet analytics needs.
• Implement data quality checks and governance practices.

Skills

Data modeling

Batch & real-time processing

Data warehouse development

Analytical thinking

Education

Bachelor's degree in Computer Science / Software Engineering / Data Engineering (or equivalent experience)

Tools

Hadoop

Spark

Iceberg

Flink

Java

Scala

Python

Job description

HappyGlobal Service is seeking an experienced Data Engineer to design, develop, and maintain scalable data warehouse solutions and processing pipelines. You will collaborate with cross-functional teams to deliver reliable data assets that drive data-driven decisions.

The ideal candidate combines strong technical skills with business understanding and can translate complex requirements into scalable data architectures. Strong knowledge of big data tech and modern data modeling is required.