Data Engineer I - Build Scalable Data Pipelines

Amazon; New York, Northern (NY, KY); Hybrid; USD 111,000 - 185,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Zappos is looking for a Data Engineer to design, build, and maintain data pipelines, ETL processes, and data warehousing solutions. You will ensure data quality and collaborate with data scientists and analysts to support analytics and machine learning initiatives.

You will work with cross-functional teams to redesign data architecture and enable scalable, reliable data infrastructure for the company's data ecosystem.

Qualifications

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with query languages such as SQL / PL/SQL / HiveQL / SparkSQL.
• Experience with scripting languages such as Python.
• Bachelor's degree.

Responsibilities

• Design, build, and maintain robust data pipelines to acquire, process, and store data from databases, APIs, and external providers.
• Develop and optimize ETL processes to clean, enrich, and structure data for analysis and reporting.
• Implement and manage data warehousing solutions for efficient storage, retrieval, and query performance.
• Establish data quality standards and perform data validation to address quality issues.
• Collaborate with data scientists and analysts to understand data requirements and provide infrastructure.

Skills

Data engineering

Data modeling

Warehousing

ETL pipelines

SQL / SparkSQL / HiveQL

Python scripting

Education

Bachelor's degree

Tools

Hadoop

Hive

Spark

EMR

Job description

Zappos is looking for a Data Engineer to design, build, and maintain data pipelines, ETL processes, and data warehousing solutions. You will ensure data quality and collaborate with data scientists and analysts to support analytics and machine learning initiatives.

You will work with cross-functional teams to redesign data architecture and enable scalable, reliable data infrastructure for the company's data ecosystem.