Data Engineer II, S&OP

Job summary
Do you love using data to solve complex supply chain problems? Are you interested in innovating and developing world-class business intelligence solutions? We have the career for you!

Amazon's Sales & Operations Planning (S&OP) team is seeking a Data Engineer to join our Analytics team. We deliver business intelligence/data science solutions to a diverse community of internal customers dedicated to supply chain optimization and forecast accuracy. Amazon has culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable.

As a Data Engineer, you will get exciting opportunity to work on large datasets in one of the world's biggest and most complex data warehouse environments. You will collaborate with business teams within Global Supply Chain organization on various process optimization initiatives, provide technical solution that will address unique business challenges.

You will be responsible for end-to-end data solution design and implementation including but not limited to data modelling, ETL, BI analytical layer. You will have an opportunity to work with leading edge AWS technologies, third-party and in-house tools.

This position requires excellent statistical and analytical abilities, deep knowledge of business intelligence solutions and data engineering practices, and the ability to partner with various teams across Amazon. The successful candidate will be a self-starter comfortable with ambiguity, capable of working in a fast-paced environment, possess a strong attention to detail, and able to collaborate with internal customers to understand and transform business problems into requirements and deliverables.

Key job responsibilities

• Contribute to the architecture, design and implementation of next generation data engineering solutions.
• Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
• Collaborate with data scientists, BIEs, BAs to deliver high quality data architecture and pipelines.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
• Develop the end-to-end automation of data pipelines, making datasets readily-consumable by visualization tools and notification systems
• Create automated alarming and dashboards to monitor data integrity.
• Create and manage capacity and performance plans

About the team
The broad mission of the S&OP team is to align and optimize the Fulfillment Center (FC) network plan for labor and capacity constraints, ideal placement and purchasing volumes. We partner with internal stakeholders to continuously improve plan accuracy, visibility and tools to automate the planning process. Every week we provide an accurate short to medium term aggregate fulfillment plan for the US and CA fulfillment network in order to make local planning decisions at the FCs.

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, or related field with a track record of manipulating, processing, and extracting value from large datasets.
• Experience in Data Modeling, ETL Development, and Data Warehousing working on multiple large scale, cross-functional projects.
• Expert-level proficiency in writing complex, highly-optimized SQL queries across large datasets.
• Experience in coding and building end-to-end solutions that enable business stakeholders, BI engineers and analysts to self-serve their business intelligence needs.

Preferred Qualifications

• Masters in computer science, mathematics, statistics, economics, or other quantitative fields
• 5+ years of experience as a Data Engineer, BI Engineer or in a similar role.
• Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
• Experience working with AWS (Redshift, S3, EMR, Glue, Airflow).
• Hands-on in any scripting language (C#, Java, Python, Perl, Typescript, Ruby).
• Proven success in communicating with users, other 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.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.