Data Engineer II, Amazon AIR

Do you want to join one of the most exciting teams at the world's most customer-centric company? Then come soar with Amazon Air! AIR DABI's vision is to offer the data infrastructure, and data applications / processes / practices to enable the AIR business to achieve its goal to leverage its capacity, speed, quality of service, and organic infrastructure to delight Amazon customers worldwide.

We are looking for an experienced, innovative Data Engineer. In this role, you will be working in a large and complex data warehouse environment.

You should be passionate about working with disparate datasets and be someone who loves to bring data together to answer business questions.

You should have deep expertise in the creation and management of datasets and the proven ability to translate the data into meaningful insights through collaboration with Analysts, Business Intelligence Engineers, Data Scientists, SDEs, as well as business teams across Amazon AIR org.

In this role, you will have ownership of end-to-end development of data engineering solutions to complex questions and you’ll play a critical role in strategic decision-making.

The right candidate will possess excellent technical ability in relational database management systems a database architecture, solid business and communication skills, be able to work with business owners to develop and define key business questions, be able to work with external data vendors to onboard new datasets, and be able to collaborate to analyze data.

Key job responsibilities

• Design, develop, and maintain new and existing data pipelines to drive key business decisions.
• Design, implement, and support a platform providing secured access to large datasets.
• Recognize and adopt best practices in data integrity, test design, analysis, validation, and documentation.
• Tune data pipelines and query performance using profiling tools and SQL.
• Analyze and solve problems at their root, stepping back to understand the broader context.
• Learn and understand a broad range of Amazon's data resources and know when, how, and which to use and which not to use.
• Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS.
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
• Design, implement, and support an analytical data infrastructure providing ad hoc access to large datasets and computing power
• Managing AWS resources
• 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
• Work with external data vendors to onboard data into existing infrastructure
• Collaborate with Analysts, Business Intelligence Engineers and Data Scientists to implement advanced analytics algorithms that exploit our rich data sets for statistical analysis, prediction, clustering and machine learning
• Help continually improve ongoing reporting and analysis processes, simplifying self-service support for customers

BASIC QUALIFICATIONS

• 3+ years of data engineering experience
• 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
• Knowledge of distributed systems as it pertains to data storage and computing
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

PREFERRED QUALIFICATIONS

• Master's degree
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• 5+ years of data engineering experience
• Excellent written and verbal communication skills
• Effective communication with senior management as well as with colleagues from operations and business backgrounds
• Ability to work on a diverse team or with a diverse range of coworkers
30+ days ago