Data Engineer, Prime Air

Key Skills

Amazon EMR, Amazon RedShift, Amazon Simple Storage Service (S3), AWS Glue, AWS Kinesis, Big Data Technology, Data Engineering, Data Mining, Data Modeling, Data pipelines, ETL frameworks, Java Programming, Lambda, Large scale data processing, Machine learning techniques, MySQL, Python Programming, SQL, Terabyte scale datasets

Job Description

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization.

We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide visible benefit to customers, this is your opportunity.

Come work on the Amazon Prime Air Team!

We are looking for an analytical, results-oriented, self-motivated, and customer-focused Data Engineer to play a key role in building critical data pipelines and analytics tools across Prime Air.

The ideal candidate will have excellent analytical abilities, outstanding business acumen and judgment, intense curiosity and strong technical skills. They are a self-starter, comfortable with ambiguity, able to think big and be creative (while paying careful attention to detail), and enjoy working in a fast-paced dynamic environment. To be successful in this role, you should have broad skills in end-to-end database design making datasets readily-consumable by visualization tools and notification systems, creating automated alarming and dashboards to monitor data integrity, creating and managing capacity and performance plans, working closely with both business & tech stakeholders to make data driven decisions, and acting as the subject matter expert for the data structure and usage.

Export Control License

• This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.

BASIC QUALIFICATIONS

• 2+ years of experience analyzing and interpreting data and experience with Redshift, Oracle, NoSQL etc.
• Experience with data modeling, data warehousing, and building ETL pipelines
• 3+ years of experience as a Data Engineer or in a similar role
• Experience in working and delivering end-to-end projects independently.
• Knowledge of distributed systems as it pertains to data storage and computing
• Experience in at least one modern object-oriented programming language (Ruby, Python, Java)
• Experience with Redshift, Oracle, NoSQL etc.
• Minimum of 5+ years of experience as a Data Engineer
• Programming skills to extract, transform, and clean large (multi-TB) data sets
• Experience in scripting for automation (e.g. Python) and advanced SQL skills.
• 5+ years of SQL experience
• Knowledge and direct experience with AWS technologies
• Experience with theory and practice of information retrieval, data science, machine learning and data mining
• Bachelor’s degree in computer science, mathematics, statistics, economics, or other quantitative field
• 5+ years of relevant work experience in a role requiring application of data modeling and analytic skills
• Demonstrated experience with ETL development, data modeling, data warehousing, tools such as MySQL and databases in a business environment with large-scale, complex datasets
• Advanced ability to draw insights from data and clearly communicate them to the stakeholders and senior management as required
• Self-driven, with demonstrated ability to deliver on ambiguous projects as well as projects/requests where the underlying data is incomplete
• Experience in gathering requirements and formulating business metrics
• Experienced working in a fast-paced, high-tech environment and comfortable navigating conflicting priorities and ambiguous problems

PREFERRED QUALIFICATIONS

• MBA or Master’s degree in Computer Science, Engineering, Statistics, Mathematics or related field
• Experience working in very large data warehouse environments
• Experience working with AWS big data technologies (EMR, Redshift, S3, Glue, Kinesis and Lambda)
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering