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Advertising is one of the fastest growing businesses within Amazon, empowering Amazon Sellers, Vendors, Authors, and Publishers to boost their product reach and sales through performance and display advertising.
The Ads Billing team (Iron Mountain) is an enabler for SA and ADSP ads worldwide rapid growth and offers a singular platform to manage all of the advertiser facing functions like billing, invoicing, accounting automation, budgets, promotions, payments, and Billing Advertiser Experience(AX) in real-time while being transparent and audit-able from the ground-up. As a part of this high-energy, entrepreneurial team you will get an opportunity to innovate on solutions that control the very levers of our advertisers' experience and have the satisfaction of seeing your work impacting multiple advertising business and bring in multi-million transactions worth 100x in dollar value on a daily basis. This platform owns these mandates for worldwide advertising displayed On or Off Amazon.
Iron Mountain team is seeking a Data Engineer to help us accelerate our efforts in delivering technology and insights capabilities to Ads Accounting and Finance teams. This role will influence the direction of the business by translating broad business problems into specific analytics projects, building and maintaining data pipelines, datasets, conducting quantitative analyses, and communicating results effectively. This individual will help drive scalable robust management of datasets and pipelines to assist Business and Finance leadership with decision-making. As a key data engineering partner, this candidate will have significant exposure to Advertising Accounting and Finance Managers, and require partnership with a broad set of teams including finance, product, sales, operations, and technology. We see a high potential for growth in the role as we transform our data into actionable insights to continue to fuel the growth of our business partners.
- Key job responsibilities
- Building data pipelines using SQL, Scala, Py Spark & Python
- Working with AWS & BDT technologies such as Glue, S3, Redshift, Datanet, Cradle, etc.
- Web-app development leveraging Flask, React or similar technologies
- Building solutions that monitor the quality of data in our pipelines (including anomaly detection)
- Ability to setup and/or manage Airflow, Maestro, LLMs
- Participating in design reviews and consulting with engineering peers
- Participating in operational support for our products, and drive reliability and process improvements
- Optimizing the performance of pipelines using metrics
- Designing and implementing complex pipelines and other Data Engineering solutions
Basic Qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, 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)
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.
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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