Level

Amazon

Data Engineer II, Amazon Key

AI in this role

Designs and operates large-scale data lake and data warehouse infrastructure using AWS big data stack to support Amazon Key.

pythonawsredshiftquicksightgluelake-formationemrsparkscalaathena
data-engineeringetldata-warehousingdata-modelingbusiness-intelligence
We are actively seeking a motivated and multi-talented individual who is passionate, highly autonomous and have deep expertise in the design, creation, and management of large and complex datasets. You should be an authority at crafting, implementing, and operating stable, scalable solutions to flow huge amounts of data from production systems into the Redshift cluster, and build complex transforms to compute and store new data developed by the software teams.

Key job responsibilities
• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Develop and manage ETLs to source data from various commercial, sales and operational systems and create unified data model for analytics and reporting.
• Use business intelligence and visualization software (e.g., QuickSight.) to develop dashboards those are used by senior leadership.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Work with Product Managers, Engineering, BI Teams on day-to-day basis to support their new analytics requirements.
• Manage numerous requests concurrently and strategically, prioritizing when necessary
• Partner/collaborate across teams/roles to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.

About the team
Amazon Key team’s mission is to provide Amazon with 1-click access to every customer's doorstep. We are inventing the next-generation smart delivery operation technologies in IoT (Internet-of-Things). We develop technology-based solutions matching customer needs and delivery capacity with precision and efficiency, and expanding and transforming delivery experience with unprecedented quality, productivity and scale.

Basic qualifications

- Bachelor's degree or foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- 3+ years of data engineering experience
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Preferred qualifications

- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- 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
- Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience using strong customer service, communication, and interpersonal skills

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, TX, Austin - 132,100.00 - 178,800.00 USD annually
USA, WA, Bellevue - 132,100.00 - 178,800.00 USD annually

How we rate this

Data Engineer II, Amazon Key at Amazon rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data EngineeringETLData WarehousingData ModelingBusiness IntelligencePythonAWSRedshift

Questions you could be asked

  1. Tell me about a project where data engineering was part of your work. What did you do?
  2. Tell me about a project where etl was part of your work. What did you do?
  3. Tell me about a project where data warehousing was part of your work. What did you do?
  4. Tell me about a project where data modeling was part of your work. What did you do?
  5. Tell me about a project where business intelligence was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Data Engineering, ETL, Data Warehousing, Data Modeling, and Business Intelligence. 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.

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