- 5+ years of experience as a Data Engineer or in a similar role
- Experience with data modeling, data warehousing, and building ETL pipelines
- Experience in SQL
- A desire to work in a collaborative, intellectually curious environment.
- Degree in Computer Science, Engineering, Mathematics, or a related field or 2+ years industry experience
- Demonstrated strength in data modeling, ETL development, and data warehousing.
- Data Warehousing Experience with Oracle, Redshift, PostgreSQL, etc.
- Query performance tuning skills
- Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)
Time and Attendance is looking for a Sr. Data Engineer to deliver data insights for cross-functional projects to eliminate employee pay defects.
Time and Attendance (TAA) is a rapidly growing team tackling new, hard problems that Amazon has not solved at scale and creating fundamentally improved ways for employees to record time and receive accurate pay. We balance start-up vision and operational excellence, technical complexity and clear product definition, and global scope across multiple Amazon businesses. We are developing software solutions to support Amazon’s high-growth populations. We’ve all heard about 24/7/365. That’s 8760 hours in a year. Now multiply that by the hundreds of thousands of hourly workers at Amazon … those who work in our fulfillment, customer service, Alexa data services, and AWS data centers; employees in our growing number of Amazon Books bookstores and subsidiaries. On every continent. We must be able to move at Amazon speed and support new and varied business launches.
Who are we looking for to join our team?
At Amazon we take seriously our commitment to pay employees accurately and on-time. While each line of business is responsible for knowing and driving down pay defects for their own employees, the centralized TAA Perfect Pay team manages data stores and analytics, program oversight, cross-org technical and non-technical projects, and drives accountability across leaders. We are looking for a Sr. Data Engineer to identify and deliver data insights for cross-functional projects involving tools and processes to prevent pay defects before they happen. The ideal candidate will have a proven ability to improve business operations using metrics and develop predictive risk analysis. They will have a track record of using data to inform product and process decisions, tech fluency, a strong capacity to earn trust, and the ability to build reporting and analysis for director and VP-level business, HR, and legal leaders across Amazon. Domain experience in time and attendance and payroll, or Amazon operations field experience, is useful but not required.
As a Sr. Data Engineer, you should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics. You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. You should have the ability to develop and tune SQL to provide optimized solutions to the business.
- Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience building data products incrementally and integrating and managing datasets from multiple sources
- Experience leading large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, etc.
- Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
- Experience with AWS