The GTS Finance Technology team is looking for a passionate, solution-oriented Data Engineer to lead the implementation of the analytical data infrastructure that will guide the decision making behind initiatives like transportation cost analytics platform and expanding cost reporting at individual product.
The team is committed to building the next generation big data platform that will be one of the largest finance data warehouses to support Amazon's rapidly growing and dynamic Transportation business.
Our projects span multiple organizations and require coordination of data integrity, test design, analysis, validation, and documentation. You will act as the business-facing subject matter expert for data storage and feature instrumentation, with the responsibility of managing end-to-end execution and delivery across various work streams.
In this role, you will be a technical expert with significant scope and impact. You will work closely with a group of Business Intelligence Engineers, Financial Analysts, Research Scientists, and Data Scientists to recreate the data infrastructure and pipelines necessary to drive Global Transportation Services initiatives. In this role, you will partner and have exposure to our technology teams in Supply Chain Optimization Technologies (SCOT), Modeling and Optimization (MOP), and with our Machine Learning Teams as they leverage our data sets to improve the effectiveness of their models.
Key job responsibilities
- Design, implement and support an analytical data infrastructure
- Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis
- Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline
- 3+ years of industry experience in Software Development, Data Engineering, Business Intelligence, Data Science, or related field with a track record of manipulating, processing, and extracting value from large datasets
- Hands-on experience and advanced knowledge of SQL
- Experience in Data Modeling, ETL Development, and Data Warehousing
- Experience using business intelligence reporting tools (Power BI, Tableau, Cognos, etc.)
- Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
- Knowledge of Data Management fundamentals and Data Storage principles
- Experience coding and automating processes using Python or R
Preferred Qualifications
- Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
- 5+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst or Systems Analyst in a company with large, complex data sources.
- Experience working with AWS big data technologies (Redshift, S3, EMR)
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- Proven success in communicating with business users, technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
- Experience providing technical leadership and educating other engineers for best practices on data engineering.
- Familiarity with statistical models and data mining algorithms.
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