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Data Engineer, Amazon Ads, ML Service



Software Engineering, Data Science
New York, NY, USA
Posted on Friday, February 9, 2024


Ad Catalyst is part of Advertiser Experience organization within Amazon Worldwide Advertising. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. The Advertiser Experience (AX) organization owns the experience of the advertiser from the moment they decide to engage with our platform through the full lifecycle of self-service advertising management. Ad Catalyst Team enables Advertisers to get most growth by providing them with science-backed ML generated guidance at-scale by connecting retail, advertising and marketing signals.

We are looking for an experienced data engineer with a track record of delivering high quality big data pipelines using AWS distributed architectures (e.g., Glue, S3, Spark, EMR, Airflow) and is a great team player who is skilled in stakeholder management. You will be working closely with cross-functional teams (science and SDE) to build robust data pipelines, optimize data processing systems, and deploy machine learning models that power our advertiser facing solutions. This role offers a unique opportunity to contribute to the intersection of data engineering and machine learning in a dynamic and collaborative environment. Your contributions will directly lead to enhanced site wide performance, growth in ad products, innovative new experiences, faster execution for engineering teams, and increased success of Amazon’s fastest growing business.

Strong candidates for this role will have strong problem-solving skills with a keen attention to detail in designing and optimizing data processing pipelines, ability to collaborate effectively with cross-functional teams, excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. If you enjoy working and growing high performance teams, being part of a rapidly growing business, and inventing creative solutions to complex problems, this role is for you!

We are open to hiring candidates to work out of one of the following locations:

New York, NY, USA

Key job responsibilities
* Design and implement scalable data pipelines for collecting, processing, and storing large volumes of data
* Collaborate with data scientists, software engineers, and domain experts to evaluate, gather and process data for model training
* Work closely with scientists to integrate machine learning models into production pipelines
* Develop and implement data quality and validation processes to ensure accuracy and reliability
* Optimize and fine-tune models for performance, scalability, and efficiency.
* Work closely with SDE teams to design data solution for API use
* Bar raising the operational excellence of data engineer practice

We are open to hiring candidates to work out of one of the following locations:

New York, NY, USA


- 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 with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Proven experience to contribute to the development of operational processes for efficient data model deployment and maintenance


- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Experience in popular machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn

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 $105,700/year in our lowest geographic market up to $205,600/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. Applicants should apply via our internal or external career site.