DESCRIPTION

Over the past 20 years, Amazon has reinvented on behalf of customers and has become the largest internet retailer in the world. Amazon is now reinventing the global supply chain and international e-commerce and is recruiting a senior data engineer to help make this vision a reality. In this role, you will be responsible for the development and improvement of Workforce Planning Analytics platform used for planning, reporting, and forecasting purposes as well as dataset management. You will get the unique opportunity to work closely with a variety of stakeholders, including Business Analysts, Site Leads, and other Program Management teams. The candidate will also be in charge of driving strategic initiatives to improve reporting efficiency, develop new bridging workflow tools and establish new key performance metrics where appropriate.
The ideal candidate will not only raise the bar on Data engineering skills but demonstrates a strong curiosity to understand the business end-to-end and be comfortable working with ambiguity. The candidate will also have an eye for detail, be proficient/advanced in SQL/DWH/Python and invent for solving data and reporting challenges. The role requires good communication skills with other functional teams.

Key job responsibilities

• Understand unique business needs, review existing tech stack and data landscape, design/re-design, implement and build an analytical data infrastructure for multiple ads businesses.
• Influence upstream and partner data teams to ensure the reliable data solutions for our team.
• Manage AWS resources including EC2, EMR, S3, Glue, Redshift, ECS etc.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
• Explore, learn and adopt the latest AWS technologies to provide new capabilities and increase efficiency.
• Collaborate with and support Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
• Work with stakeholders to understand the business questions and define requirements and build out scalable data solutions.
• Support and continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

A day in the life
You will work closely with senior leaders across cross-functional stakeholder teams within Amazon to drive collaboration and influence them to prioritize projects, meet objectives, and adhere to business plans towards shared objectives.
If you are not sure that every qualification on the list above describes you exactly, we’d still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k)

BASIC QUALIFICATIONS

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices

PREFERRED QUALIFICATIONS

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses
  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.
  Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site

• Understand unique business needs, review existing tech stack and data landscape, design/re-design, implement and build an analytical data infrastructure for multiple ads businesses.
• Influence upstream and partner data teams to ensure the reliable data solutions for our team.
• Manage AWS resources including EC2, EMR, S3, Glue, Redshift, ECS etc.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
• Explore, learn and adopt the latest AWS technologies to provide new capabilities and increase efficiency.
• Collaborate with and support Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
• Work with stakeholders to understand the business questions and define requirements and build out scalable data solutions.
• Support and continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers