Level

Amazon

Business Analyst Support

AI in this role

Build and maintain SQL data pipelines, automate processes with Python, and provide business analytics support.

sqlpythonexcelrsasspss
data-pipelinesetlautomationbusiness-intelligence
The candidate would be responsible for creating/maintaining complex SQL queries and scheduling/refreshing ETL jobs. They would be required to automate manual tasks and simplify them using Python. They would also be required to build data pipelines/dashboards, take up dive deep requests, make changes to existing analytical framework and provide data support to concerned stakeholders. The person should have a good understanding of a business requirement and the ability to quickly get to the root cause of a particular reporting/BI/data issue and draft solutions for resolution specially during high demand period like OP/3YF planning. The ideal candidate would be high on attention detail, show bias for action and keen interest in analytics/BI/automation.

Some of the key result areas include, but not limited to:

Own the design, development and maintenance of ongoing data pipelines, queries, metrics, reports, analyses, dashboards, etc. to drive key business decisions. Ensure data accuracy by validating data for new and resources.
Work closely with stakeholders (internal/external) to understand and automate/enhance the existing processes.
Should be open to learn and develop skillsets in the latest data and AWS technologies and analytical techniques
Should be able to solve a business problem through a solution driven by data.
Should be able to come up with innovative ideas for new work or to improve existing work.

About the team
Rest of World (RoW) Supply Chain Analytics, Research and Product (SHARP) team supports supply chain processing for the multiple geographies like IN, Japan, Mexico, Brazil, MENA, AU & SG.

Basic qualifications

- 2+ years of data analytics or automation experience
- Knowledge of SQL/Python/R, scripting, MS Excel, table joins, and aggregate analytical functions
- Experience with data mining tools like SQL, SAS, SPSS, or similar

Preferred qualifications

- Knowledge of data pipelining and extraction using SQL

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.

How we score this

Business Analyst Support at Amazon scores 0 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands 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 PipelinesEtlAutomationBusiness IntelligenceSqlPythonExcelR

Questions you could be asked

  1. Tell me about a project where data pipelines 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 automation was part of your work. What did you do?
  4. Tell me about a project where business intelligence was part of your work. What did you do?
  5. Walk me through how you've used Sql in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Data Pipelines, Etl, Automation, Business Intelligence, and Sql. 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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