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Data Engineer III, Partner Experience and Growth, Amazon Ads

DescriptionAmazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Partner Experience and Growth (PEG) organization leverages advanced analytics and experimentation to unlock value for our advertising partners and mutual customers, i.e. the advertisers.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 strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact.Key job responsibilitiesDesign, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.Implement data ingestion routines both real time and batch 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.Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.About The TeamData Engineering team focuses on helping other partner business teams to be a more data driven business. We synthesize data from various data sources into actionable information, help the team to build the insights and take business decisions. We maintain partner data platform(Barnegat) and support end to end data engineering needs for our customers. Data engineering team customers include Analytics, Science, Finance, Partner Trust, Business Development, Product and other Advertisement teams. Our core services are managing Data platform, data pipelines to get data from various sources, create scalable and reusable datasets and provide single source of truth for business metrics.Basic Qualifications• 5+ years of data engineering experience• Experience with data modeling, warehousing and building ETL pipelines• Experience with SQL• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS• Experience mentoring team members on best practicesPreferred Qualifications• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR• Experience operating large data warehouses• 7+ years of data engineering, database engineering, business intelligence or business analytics experience• Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent• Experience in working with data, analytics and reporting related to risk management, fraud detection, and customer trust/identity verification.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.Company - Amazon.com Services LLCJob ID: A2839853

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What You Should Know About Data Engineer III, Partner Experience and Growth, Amazon Ads, Amazon

Are you ready to take your career to the next level with Amazon as a Data Engineer III in our Partner Experience and Growth team? Located in the vibrant city of Seattle, WA, this role is all about driving innovation in one of Amazon's fastest-growing and most profitable businesses: Worldwide Advertising. As a Data Engineer, you'll have the exciting opportunity to lead technical initiatives and create end-to-end analytical solutions that help our advertising partners unlock substantial value. You'll design and implement high-performance data structures that are not only scalable and robust but also secure and cost-effective. Collaboration is key in this role, as you’ll work closely with engineers and scientists to develop cutting-edge algorithms and best practices. If you're passionate about simplifying complex data systems and committed to delivering customer-focused solutions, we want to hear from you! You'll gather business requirements, create adaptable data architectures, and continually improve our reporting processes—all while operating at the frontier of big data technologies. Join us in our mission to synthesize data from diverse sources and help teams make data-driven decisions. Your journey at Amazon will not just be about data; it will be about making a significant business impact alongside a diverse and inclusive team.

Frequently Asked Questions (FAQs) for Data Engineer III, Partner Experience and Growth, Amazon Ads Role at Amazon
What are the main responsibilities of a Data Engineer III at Amazon?

As a Data Engineer III at Amazon, you'll be responsible for designing and implementing high-volume data structures for analytics and data science. This includes developing real-time and batch data ingestion processes using AWS technologies, gathering business requirements, and collaborating with engineers to establish best practices in data integrity and documentation.

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What qualifications are needed for the Data Engineer III position at Amazon?

To qualify for the Data Engineer III role at Amazon, you should have a minimum of 5 years of data engineering experience, proficiency in data modeling and ETL pipeline construction, and strong SQL skills. Experience with data technologies like Hadoop or Spark is preferred, along with a master's degree in a relevant field being a bonus.

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What technologies do Data Engineer IIIs at Amazon typically work with?

Data Engineer IIIs at Amazon frequently work with AWS technologies and big data tools, including Hadoop, Hive, Spark, and EMR. Proficiency in a modern programming language such as Python, Java, or Scala is also essential for creating scalable data solutions.

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Is mentoring a part of the Data Engineer III role at Amazon?

Yes! Mentoring is an important aspect of the Data Engineer III position at Amazon. You’ll have the opportunity to mentor team members on best practices in data engineering, ensuring that the team remains at the forefront of data solutions and development.

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What is the work culture like for a Data Engineer III at Amazon?

The work culture for a Data Engineer III at Amazon is dynamic and inclusive. You’ll be part of a team that thrives on collaboration and innovation, where diverse perspectives are valued, and every team member has the chance to contribute to impactful projects. Amazon fosters an environment that supports continuous learning and development.

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Common Interview Questions for Data Engineer III, Partner Experience and Growth, Amazon Ads
Can you describe your experience with ETL pipelines as a Data Engineer III?

In answering this question, focus on specific ETL projects you've worked on. Detail the tools and methodologies you employed, such as data extraction methods, transformation processes, and loading techniques. Highlight what challenges you encountered and how you overcame them to optimize these pipelines.

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How do you ensure data integrity in your engineering practices?

Discuss the strategies you implement to maintain data integrity, such as validation techniques during data ingestion, rigorous testing protocols, and adherence to best practices in data documentation. Provide examples from your work experience that illustrate your commitment to data quality.

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What is your approach to collaborating with data scientists at Amazon?

Emphasize your experience in cross-functional collaboration. Share specific instances where you worked closely with data scientists to develop algorithms or analytical models, highlighting any tools or frameworks you used, and the impact of your collaborative efforts on project outcomes.

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Describe a complex data architecture you've built. What challenges did you face?

Provide a detailed description of the data architecture, including its purpose and components. Talk about the challenges encountered—such as scalability or integration issues—and how you addressed them. This showcases both your technical skills and problem-solving abilities.

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What big data technologies are you most comfortable with?

List the big data technologies you’ve worked with, such as Hadoop, Spark, or Kafka. Explain how you utilized these technologies in your projects and the results you achieved. This can give an interviewer insight into your technical expertise and comfort with handling large datasets.

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How do you stay current with advancements in data engineering?

Share your strategies for maintaining industry knowledge, such as following relevant blogs, participating in webinars, or attending industry conferences. Mention any certifications you’ve pursued to further your knowledge, showcasing your commitment to continuous learning.

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Can you give an example of a time you optimized a data process?

Detail a specific instance where you enhanced a data processing workflow. Outline the steps you took, the tools used, and the metrics that demonstrate the improvement, such as reduced processing time or increased accuracy. This illustrates your analytical and technical skills.

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What factors do you consider when designing a data model?

Discuss the key factors you evaluate, such as scalability, data integrity, and the end-user requirements. Provide examples from your experience that illustrate how these considerations have influenced your past projects, demonstrating your critical thinking and planning skills.

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What experience do you have with mentoring junior engineers?

Highlight your role in mentoring, discussing how you've guided junior engineers through challenges, shared knowledge, and contributed to their professional growth. Provide examples of successful mentorship outcomes to illustrate your leadership abilities.

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How do you balance business needs with technical constraints?

Explain your approach to understanding business requirements while staying grounded in technical feasibility. Share examples of situations where you successfully bridged the gap between stakeholder needs and technical limitations, ensuring both sides were satisfied.

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Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking.

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CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
BENEFITS & PERKS
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
INDUSTRY
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
November 30, 2024

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