The Data Engineer on the Engineering Services Business Intelligence Team will be the designer and architect for developing a data system that can be scaled globally to support Engineering Services. The Engineering Services organization is responsible for delivering capacity to the Amazon Fulfillment network, including planning, configuration management, design, construction, startup, procurement, launch, and operations engineering teams. In this role, the DE would also perform and support financial and operational analyses, surfacing opportunities to reduce cost and innovate. The DE improves business processes, leverages strong data extraction skills to engineer reporting mechanisms, and support budget planning. The individual must have the ability to communicate effectively across multiple technical and non-technical teams, as well as across other geographies. Successful members of this team collaborate effectively to solve problems, implement new solutions, and deliver successfully against high operational standards.
The successful candidate will have strong data mining and modeling skills and is comfortable facilitating ideation and working from concept through to execution. This role will also build tools and support structures needed to analyze data. As a Data Engineer in this team, you will be responsible for developing the data architecture components that scales for the ever-evolving data needs. You will solve big data warehousing problems on a massive scale. You will apply cloud-based AWS services to solve challenging problems around: big data processing, data warehouse design, and enabling self-service. You will focus on automation and optimization for all areas of DW/ETL maintenance and deployment. You will work closely with the business intelligence engineers, and the software development teams on many non-standard and unique business problems and use creative problem solving to deliver actionable output. The role of a Sr. data engineer in Amazon requires excellent technical skills in order to develop systems and tools to process data as well as, but not limited to, the ability to analyze data.
A qualified candidate must have demonstrated ability to manage medium to large-scale data modeling projects, identify requirements and tools, build data warehousing solution and tools that are explainable and scalable. In addition to the technical skills, possess strong written and verbal communication skills, strong focus on internal customers and professional demeanor and high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise.
Core responsibilities may include:
· Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power
· 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
· Be enthusiastic about building deep domain knowledge about Amazon’s business and the fulfillment quality space.
· Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
· Enjoy working closely with your peers in a group of very smart and talented engineers.
· Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
· Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
· Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline
· Industry experience in Data Engineering, BI Engineer, or related field
· Track record of data management fundamentals and data storage principles
· Hands-on experience and advanced knowledge of SQL, Python etc.
· Demonstrated strength in data modeling, ETL development, and data warehousing
· Knowledge of distributed systems as it pertains to data storage and computing
· 2+ years of experience as a Data Engineer, BI Engineer, or Systems Analyst in a company with large, complex data sources.
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
· Experience working with AWS big data technologies (EMR, Redshift, S3, Glue, Kinesis and Lambda)
· 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 mentoring other engineers for best practices on data engineering
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
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