Data Engineer, Machine Learning & Engineering, Science and Technology
Amazon’s ATS Machine Learning & Engineering team is looking for a data-driven and customer-obsessed Data Engineer.
As a Data Engineer, you will work on designing, building, and supporting scalable data infrastructure solutions in a large, complex data environment.
Responsibilities include:
1. Contributing to development and performance improvement of AI/ML models through implementation of robust data pipelines
2. Integrating data from diverse sources and making data accessible for reporting, analysis, machine learning, and ad-hoc requests
3. Implementing solutions to aggregate data and enable fast yet secure data retrieval
4. Curating quality data that meets business needs
5. Collaborating with cross-functional teams including business owners and technology leaders to understand requirements, design technical solutions, and develop pipelines and datasets
6. Staying up-to-date on emerging technologies in the data space and evaluating new technologies for potential implementation
7. Contributing to system scalability, reliability, and efficiency
We welcome people with diverse backgrounds who meet the required skills and qualifications. Excellent communication and collaboration abilities are valued to work closely with stakeholders across the organization. Relevant experience with current big data technologies is preferred. We provide opportunities to gain exposure to cutting-edge AWS services and encourage professional development.
Key job responsibilities:
1. Contribute to the architecture, design, and implementation of next-generation Data solutions
2. Manage AWS resources including EC2, ECS, Lambda, Redshift, etc.
3. Collaborate with applied scientists, business intelligence engineers, and software development engineers to deliver high-quality data architecture and pipelines
4. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
5. Make large and/or complex data more accessible, understandable and usable by implementing advanced BI dashboards and applications
6. Own the design, development, and maintenance of metrics, reports, analyses, dashboards, etc. to drive key business decisions
A day in the life:
Our Data Engineers build and maintain the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems (e.g., MapReduce, MPP architectures, NoSQL database).
About the team:
The Machine Learning & Engineering team within the EU ATS Science and Technology organization focuses on delivering innovative solutions to Amazon's most complex forecasting and planning problems. The team is composed of a mix of DEs, SDEs, BIEs, and Applied Scientists who work together to launch state-of-the-art AI/ML models for Amazon transportation planning.
Minimum Qualifications:
1. Experience in data engineering
2. Experience with data modeling, warehousing and building ETL pipelines
3. Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
4. Experience with one or more scripting languages (e.g., Python, KornShell)
5. Knowledge of AWS Infrastructure
6. Experience with big data technologies such as Hadoop, Hive, Spark, EMR
7. Experience with any ETL tool like Informatica, ODI, SSIS, BODI, Datastage, etc.
8. Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
#J-18808-Ljbffr