Amazon
Bogota, Colombia9h ago
copilotdatabricksdata-governance+1
Data Engineer II, Intl. Seller Services
Amazon is hiring a Data Engineer II, Intl. Seller Services in Seattle, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Level.
Level's read on this job
- Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
- The posting mentions AWS, ETL and Olap among its tools and skills.
- Level classes it as a mid-level role.
- Amazon has 22,000+ other open roles on Level.
- This posting went up in the last few days.
AI in this role
Design and build scalable data and ML infrastructure to power generative AI applications for international seller services.
awsetlolapgenerative-ai
ai-researchdata-engineeringmachine-learningbig-datadata-modeling
ISS is seeking a highly motivated, experienced Data Engineer to help design and build the next generation of Data and ML infrastructure to power GenAI applications.
We are a team of Data Engineers working closely with Applied Scientists, Data Scientists, and Economists—turning machine learning, deep learning, and AI research into scalable products that delight our customers worldwide.
ISS is seeking a highly motivated, experienced Data Engineer to help design and build the next generation of Data and ML infrastructure to power GenAI applications.
Key job responsibilities
As a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective.
You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems.
You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
Implement data ingestion routines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
Identify opportunities in existing data solutions for improvements
Basic qualifications
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
- 3+ years of in the job offered or a related occupation experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
- Experience with data modeling, warehousing and building ETL pipelines
Preferred qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually
How we rate this
Data Engineer II, Intl. Seller Services at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Classification
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
AI ResearchData EngineeringMachine learningBig DataData ModelingAWSETLOlap
Pay
- This job starts at
- $132k
- Typical data engineer job
- $150k
This posting starts 12% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where big data was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Data Engineering, Machine learning, Big Data, and Data Modeling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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