As a software development engineer fthe Diags-Systems team, you will be responsible fsupporting testing of low level drivers firmware in a fast paced, dynamic environment. Prospective candidates will be hands-on engineers who will design develop test processes tools to run on off target. This will require collaboration with your partners in Development Quality to help define execute the test strategies inder to deliver high quality products. In addition, you will work with teams of industry-leading innovators across acoustics, mechanical engineering, software engineering, hardware engineering, user experience. If you love music, solving challenging problems delivering high-quality products, we want to talk with you!
What You’ll Do
1，Design execute test cases to support low level driver development, this may require creative approaches fautomating physical interactions with units under test.
2，Develop new tools scripting to aid in test execution.
3，Support new board bring up manufacturing line testing
4，Triage maintain existing automation testbeds
5，Work with manual test engineers to develop automation around repetitive, manual test cases
6，Work with team members to develop strategies freliability testing of the HW/SW interaction layer
7，Work with team members to develop strategies fAPI testing of the abstraction layer used by user space applications
What You’ll Need
Basic Qualifications
1，Bachelors Degree in Computer Science, Computer Engineering, Electrical Engineering equivalent experience
2，Basic proficiency in C/C++
3，Basic understanding digital electronics embedded systems
4，Basic familiarity with low level communication protocols like I2C, PCIe, USB
5，Understanding of GIT as a source code management system
6，Experience using logic analyzers other digital electronics test tools
7，Experience developing fLinux
8，Can work in English.
Preferred Qualifications
1，Strong C/C++ development skills
2，Experience in Linux kernel development
3，Basic understanding of 802.11 networking and/experience using tools like WireShark fnetwork traffic analysis
4，Experience in testing IoT/Embedded systems (Preferably in a Linux environment)
5，Experience with Jenkins
6，F(xiàn)amiliarity with Python Pytest
7，Interest in DIY IoT robotics projects
更新于 2026-01-19
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Amazon Global Selling has been helping individuals businesses increase sales reach new customers around the globe. Today, more than 50% of Amazons total unit sales come from third-party selection. The Global Selling team in China is responsible frecruiting local businesses to sell on Amazon’s 19+ overseas marketplaces supporting local Sellers’ success growth on the Amazon. Our vision is to be the first choice fall types of Chinese business to go globally.
The Amazon Global Selling Analytics, Intelligence, Technology (AGS-AIT) team serves as the research, automation, insight arm of the International Seller Service data hub, enabling rapid delivery of growth insights through strategic investments in regional data foundations, self-service business intelligence solutions, artificial intelligence tools.
The AGS-AIT team is positioned to establish AI-ready foundational capabilities across the AGSganization while maintaining excellence in business insight generation, self-service BI/AI application development.
AGS-AIT is looking fa Data Engineer to collaborate with cross-functional teams to design develop data infrastructure analytics capabilities fAGS AI Automation initiatives.
Key job responsibilities
? Design implement end-to-end data pipelines (ETL) to ensure efficient data collection, cleansing, transformation, storage, supporting both real-time offline analytics needs.
? Develop automated data monitoring tools interactive dashboards to enhance business teams’ insights core metrics (e.g., user behavior, AI model performance).
? Collaborate with cross-functional teams (e.g., Product, Operations, Tech) to align data logic, integrate multi-source data (e.g., user behavior, transaction logs, AI outputs), build a unified data layer.
? Establish data standardization governance policies to ensure consistency, accuracy, compliance.
? Provide structured data inputs fAI model training inference (e.g., LLM applications, recommendation systems), optimizing feature engineering workflows.
Basic qualifications
1+ years of data engineering experience
Experience with data modeling, warehousing building ETL pipelines
Experience with one more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
Experience with one more scripting language (e.g., Python, KornShell)
Preferred qualifications
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, IAM roles permissions
更新于 2026-01-26
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