Data Engineer

Cypress HCM; San Jose (CA); Hybrid; USD 78,431 - 111,705; Part time

Job summary

Cypress HCM is seeking a Data Engineer to support Growth Monetization initiatives in San Jose, CA. The ideal candidate will have at least 5 years of data engineering experience, strong SQL skills, and hands-on experience with Big Data technologies. This contract role emphasizes building scalable data pipelines and collaborating with cross-functional teams for data-driven insights.

The position offers a competitive pay rate of up to $69.01 per hour in a hybrid work environment.

Qualifications

• Minimum 5 years of data engineering experience.
• Strong SQL expertise with experience in large datasets.
• Hands-on experience with Big Data technologies.
• Experience in building scalable data pipelines.
• Experience in developing ETL/ELT workflows.

Responsibilities

• Design, build, optimize, and maintain scalable data pipelines.
• Write complex SQL queries for experimentation analysis.
• Develop ETL/ELT workflows for large datasets.
• Improve pipeline performance and data quality.
• Process high-volume datasets using distributed technologies.
• Build monitoring and validation frameworks for data integrity.
• Partner with cross-functional teams to deliver data solutions.
• Identify and resolve data quality and performance issues.

Skills

SQL expertise

Big Data technologies (Hadoop, Hive, Spark)

Data pipeline design

ETL/ELT workflows

Collaboration skills

Job description

Job Details

• Team: US Digital Global Digital Commerce
• Data Engineer 1 (Contract)
• Location: San Jose, CA 95110 (Hybrid)
• Duration: 6/08/2026 to 11/20/2026

Job Description

Support Growth Monetization initiatives by building and optimizing scalable data pipelines that enable experimentation, analytics, and business insights.

This role is heavily focused on large-scale data engineering, SQL-driven experimentation analysis, and building reliable data infrastructure that supports cross-functional teams including Product, Data Science, Marketing, and Engineering.

Responsibilities

• Design, build, optimize, and maintain scalable data pipelines supporting Growth Monetization initiatives
• Write complex SQL queries to analyze A/B testing and experimentation results
• Develop and enhance ETL/ELT workflows for large-scale structured and unstructured datasets
• Improve pipeline performance, reliability, scalability, and overall data quality
• Process high-volume datasets using distributed data processing technologies
• Build automated monitoring, alerting, and validation frameworks for pipeline health and data integrity
• Partner with Data Science, Product, Marketing, and Engineering teams to deliver scalable data solutions and actionable insights
• Identify and resolve data quality, performance, and operational issues across data platforms

Required Qualifications

• Minimum 5 years of data engineering experience
• Strong SQL expertise with experience writing and optimizing complex queries against large datasets
• Hands‑on experience with Big Data technologies such as Hadoop, Hive, Spark, or similar distributed processing frameworks
• Experience building and optimizing scalable data pipelines in cloud or enterprise environments
• Experience developing ETL/ELT workflows and orchestration processes
• Experience with pipeline monitoring, data validation, and performance tuning
• Strong collaboration skills and ability to work with both technical and business stakeholders
• Experience supporting experimentation, analytics, or data-driven decision making environments is highly preferred

Compensation

• Pay Rate: Up to $69.01 per hour