AmazonPosted 1w ago

Data Engineer, Workforce Solutions - Talent Mobility

Data Engineer, Workforce Solutions - Talent Mobility at Amazon scores 10 out of 100 on AI centrality, which makes it a Level 1 role on this board.

Remote (US, WA, Bellevue)midfull-time$101k-$160k

AI in this role

Design and operate data warehouses and automated pipelines to support data science and analytics teams at Amazon.

sqlnosqlpythonspark

data-warehousingetldistributed-systemsdata-modeling

Shape Amazon's Future through Innovative Hiring Technology! Join Workforce Solutions and become a key player in Amazon's continued growth and innovation. As part of this dynamic organization, you'll be at the forefront of creating industry-leading interviewer experiences and developing powerful, yet lightweight global recruiting solutions that are critical to Amazon's expansion and the launch of new products and services. In this role, you'll immerse yourself in every facet of the software development lifecycle, from initial design to final deployment and ongoing operations. Your contributions will be integral to crafting robust feature sets, intuitive designs, and user-friendly interfaces that empower Amazonians to excel in recruiting the world's top talent. We're seeking a self-driven professional with strong communication skills who can deliver high-quality results in our fast-paced environment.

Key job responsibilities
As a Data Engineer, you will/may:
• Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.
• Design data schema and operate internal data warehouses and SQL/NoSQL database systems.
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards that engineers, analysts, and data scientists use to drive key business decisions.
• Monitor and troubleshoot operational or data issues in the data pipelines.
• Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.
• Develop code based automated data pipelines able to process millions of data points.
• Improve database and data warehouse performance by tuning inefficient queries.
• Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.
• Provide assistance with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.

A day in the life
We’re on the lookout for the curious, those who think big and want to define the world of tomorrow. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.

About the team
Workforce Solutions (WS) empowers our customers by providing integrated, people-focused solutions that streamline hiring processes for WW Stores, AWS, Devices, and Talent Acquisition. As stewards of the employee lifecycle and experience, we drive initiatives that promote transparency and efficiency in career mobility, workforce engagement, and operational needs management. We prioritize customer-centricity by tailoring our capabilities and processes to align with their preferences and behaviors. Our approach is to start with the customer's needs and match individuals to the right opportunities through our services.

Basic qualifications

- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)

Preferred qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

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, Bellevue - 101,300.00 - 160,000.00 USD annually

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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 WarehousingEtlDistributed SystemsData ModelingSqlNosqlPythonSpark

Questions you could be asked

Tell me about a project where data warehousing was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where distributed systems 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?
Walk me through how you've used Sql in your day-to-day work.

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List these exact terms on your resume: Data Warehousing, Etl, Distributed Systems, Data Modeling, 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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