Data Engineer — Marketing Insights & Tech Pipelines

Amazon Advertising LLC

New York (NY)

On-site

USD 111,000 - 185,000

Full time

5 days ago
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Benefits offered by this job

Sign-on payments
RSUs
Health insurance (medical, dental, vis
401(k) matching
Paid time off
Parental leave

Job summary

Amazon Advertising LLC is seeking a Data Engineer to design and operate data integration, pipelines, and lake solutions enabling reliable advertising insights. The role emphasizes scalable data modeling, integration with AWS data platform solutions, and ongoing improvements to data quality and documentation.

Join the MINT team in New York, onsite, contributing to data artifacts, pipelines, and collaborative engineering standards while leveraging AWS Glue, EMR, Redshift, and Airflow.

Qualifications

  • 1+ years of data engineering experience.
  • Experience with data modeling, data warehousing, and building ETL pipelines.

Responsibilities

  • Develop and maintain data integration components, data pipelines, and data lake solutions.
  • Build scalable data models that support analytics, BI, engineering, and agentic workflows.
  • Partner with cross-functional teams to deliver customer solutions.
  • Improve existing data pipelines within AWS data platform solutions (Datanet/Cradle) and data services.
  • Document data artifacts and promote team learning.

Skills

Data engineering
Data modeling
Data warehousing
ETL pipelines
SQL
PL/SQL
DDL
MDX
HiveQL
SparkSQL
Scala
Python
KornShell

Tools

SQL
PL/SQL
DDL
MDX
HiveQL
SparkSQL
Scala
Python
KornShell
Hadoop
Hive
Spark
EMR
Redshift
S3
AWS Glue
Kinesis
FireHose
Lambda
IAM roles
Datanet
Cradle
Glue
Airflow

Job description

Amazon Advertising LLC is seeking a Data Engineer to design and operate data integration, pipelines, and lake solutions enabling reliable advertising insights. The role emphasizes scalable data modeling, integration with AWS data platform solutions, and ongoing improvements to data quality and documentation.

Join the MINT team in New York, onsite, contributing to data artifacts, pipelines, and collaborative engineering standards while leveraging AWS Glue, EMR, Redshift, and Airflow.

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