Data Engineer I, Zappos Analytics

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

As a Data Engineer at Zappos, you will play a crucial role in designing, developing, and maintaining our data infrastructure. You will work closely with cross-functional teams to ensure that data is collected, processed, and made available for analysis, reporting, and machine learning applications. Your expertise in data pipelines, ETL processes, and data warehousing will be instrumental in shaping our data ecosystem. The right candidate will be excited by the opportunity to redesign our company's data architecture to support our next generation of data initiatives.

Key job responsibilities

• Design, build, and maintain robust data pipelines to acquire, process, and store data from various sources such as databases, APIs, and external data providers.
• Develop and optimize ETL (Extract, Transform, Load) processes to clean, enrich, and structure raw data into a usable format for analysis and reporting.
• Implement and manage data warehousing solutions to ensure efficient data storage, retrieval, and query performance.
• Establish data quality standards, perform data validation, and proactively identify and address data quality issues.
• Optimize data pipelines and storage solutions to handle large volumes of data while maintaining high performance and reliability.
• Ensure data privacy and security by implementing access controls, encryption, and compliance with data protection regulations.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide the necessary data infrastructure to support their needs.
• Maintain comprehensive documentation for data pipelines, data models, and processes to facilitate knowledge sharing and troubleshooting.
• Implement monitoring solutions to proactively detect and address data pipeline failures or performance bottlenecks.
• Keep abreast of industry trends and emerging technologies in data engineering to recommend and implement improvements to our data infrastructure.

A day in the life

• Design, build, and maintain robust data pipelines to acquire, process, and store data from various sources such as databases, APIs, and external data providers.
• Develop and optimize ETL (Extract, Transform, Load) processes to clean, enrich, and structure raw data into a usable format for analysis and reporting.
• Implement and manage data warehousing solutions to ensure efficient data storage, retrieval, and query performance.
• Establish data quality standards, perform data validation, and proactively identify and address data quality issues.
• Optimize data pipelines and storage solutions to handle large volumes of data while maintaining high performance and reliability.

The Zappos Analytics team transforms data into actionable insights, empowering business partners to make data-driven decisions that drive profitability and growth. We develop performance metrics and visualizations using various data sources across the organization. Working with AWS technologies, you'll collaborate with cross-functional teams to solve challenging business problems and help stakeholders gain valuable insights quickly and effectively.

Basic Qualifications:

• 1+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)
• Bachelor's degree

Preferred Qualifications:

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
• Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
• Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support,