Data Engineer I, Zappos Analytics

Full 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.

About the team 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, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 111,400.00 - 185,000.00 USD annually

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