Data Engineer I: Pipelines & Warehousing

Zappos.com LLC; New York (NY); On-site; USD 110,000 - 160,000; Full time

Job summary

Zappos.com LLC is seeking a Data Engineer to design, build, and maintain our data infrastructure, ensuring data is captured, processed, and available for analytics, reporting, and ML applications. You will collaborate with cross‑functional teams to implement robust data pipelines, ETL processes, and data warehousing, while prioritizing data quality, privacy, and performance.

The role focuses on redesigning our data architecture to support next‑generation data initiatives, with opportunities to

Qualifications

• 1+ years of data engineering experience, building data pipelines and ETL workflows.
• Experience with data modeling, warehousing, and scalable architectures.
• Proficiency in SQL and Python for data processing and automation.
• Bachelor's degree in a related field.

Responsibilities

• Design, build, and maintain data pipelines to collect and process data from multiple sources.
• Develop ETL processes to clean, enrich, and structure data for analysis and reporting.
• Implement and manage data warehousing solutions to improve storage and query performance.
• Establish data quality standards and validate data integrity across systems.
• Collaborate with data scientists and analysts to support data needs.
• Maintain documentation and monitor pipelines for reliability and issues.

Skills

Data modeling

ETL pipelines

SQL

Python

AWS services

Data warehousing

Education

Bachelor's degree in a technical field

Tools

AWS

Hadoop

Hive

Spark

Snowflake

Job description

Zappos.com LLC is seeking a Data Engineer to design, build, and maintain our data infrastructure, ensuring data is captured, processed, and available for analytics, reporting, and ML applications. You will collaborate with cross‑functional teams to implement robust data pipelines, ETL processes, and data warehousing, while prioritizing data quality, privacy, and performance.

The role focuses on redesigning our data architecture to support next‑generation data initiatives, with opportunities to