Data Engineer III: ETL Pipelines & Dashboards

Pride Global; Menlo Park (CA); Hybrid; USD 192,864,000 - 264,499,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) retirement savings

Life & disability insurance

Employee assistance program

Legal support

Job summary

Pride Global is seeking a Data Engineer III to design, build, and maintain scalable data pipelines in a hybrid Bay Area setting. You will collaborate with Data Science and Product teams to ensure data quality and reliable metrics while maintaining production-grade Hive/Presto tables and robust documentation.

The role emphasizes optimizing queries, maintaining dashboards (Unidash), and supporting cross-functional analytics with strong Python and SQL skills.

Qualifications

• Requires a Bachelor’s degree in a quantitative field.
• 3+ years in data/analytics engineering.
• Strong SQL proficiency (Presto/Hive/SparkSQL).
• Experience building data pipelines with orchestration tools (Airflow, Dataswarm).
• Python or similar scripting language.
• Knowledge of data warehousing concepts and dimensional modeling.
• Strong problem-solving and data quality focus.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using Dataswarm, Spark, and related tools.
• Build and maintain dashboards and reporting tools (Unidash, internal BI platforms).
• Partner with Data Scientists and Product teams to ensure data quality and metric integrity.
• Develop and maintain production-grade Hive/Presto tables with documentation and SLAs.
• Monitor pipeline health, troubleshoot data quality issues, and implement alerts.
• Optimize query performance and data models for efficiency at scale.
• Support ad-hoc data requests and enable self-serve analytics for cross-functional partners.

Skills

SQL

Python

Airflow

ETL/ELT pipelines

Education

Bachelor's degree in Computer Science/Engineering/Mathematics

Tools

Spark

Dataswarm

Unidash

Hive/Presto

Job description

Pride Global is seeking a Data Engineer III to design, build, and maintain scalable data pipelines in a hybrid Bay Area setting. You will collaborate with Data Science and Product teams to ensure data quality and reliable metrics while maintaining production-grade Hive/Presto tables and robust documentation.

The role emphasizes optimizing queries, maintaining dashboards (Unidash), and supporting cross-functional analytics with strong Python and SQL skills.