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27d ago

Data Engineer, Prime Video - GSS Planning & Strategy

Amazon.com Services LLC Seattle, WA

Seattle, WA

27d ago

$132k - $179k/yr Full time Amazon Quicksight Analytics AWS

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Job Description

Amazon's Prime Video Global Operations is seeking a Data Engineer to design and scale data infrastructure, pipelines, and AI-enabled analytics that empower marketing, finance, and cross-functional teams. This onsite role in Seattle, WA offers a salary range of USD 132,100 to 178,800 per year and requires a bachelor’s degree along with a minimum of three years of data engineering experience. The position centers on building robust data solutions that drive critical business insights and operational decisions.

Responsibilities

Design, develop, and maintain scalable data pipelines and ETL/ELT processes to ingest, transform, and deliver data for reporting and analytics needs.
Architect data infrastructure for agentic AI and Model Context Protocols (MCP), including structured pipelines, usage data capture, and systems supporting AI-enabled self-service analytics and reporting.
Build and maintain data lakes, data warehouses, and APIs to ensure reliable, performant access to clean, governed data; optimize storage, query performance, and AWS infrastructure costs.
Create logical data models that drive physical design, enabling BI and analytics teams to build self-service reporting on a solid foundation and support forecasting at scale.
Establish data quality frameworks, monitoring, and alerting to ensure accuracy, completeness, and freshness; drive governance practices including lineage, documentation, and access controls.
Own instrumentation strategy for key platforms, ensuring comprehensive data capture across operational workflows.
Partner cross-functionally with BI engineers, analysts, operations, science, and tech teams to translate data requirements into scalable solutions.

Requirements

Bachelor’s degree in business, engineering, statistics, computer science, mathematics, or a related field.
3+ years of data engineering experience.
3+ years working with big data technologies such as Hadoop, Hive, Spark, or EMR.
Experience with data modeling, warehousing, and building ETL/ELT pipelines.
4+ years of experience with one or more query languages (SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala).
Experience using Python or another scripting language for data processing.
Knowledge of data schema design, including normalization, relational models, and dimensional models.
Strong cross-team collaboration skills and effective written and verbal communication when interfacing with stakeholders, peers, and executives.
Understanding of professional software engineering practices for the full software development lifecycle, including coding standards, code reviews, version control, continuous deployment, testing, and operational excellence.
Experience using BI tools (e.g., Tableau, QuickSight) to visualize data.

Technologies

Hadoop
Hive
Spark
EMR
SQL
PL/SQL
DDL
HiveQL
SparkSQL
Scala
Python
Tableau
QuickSight
S3
Redshift
SageMaker
Kinesis
Lambda
EC2
Informatica
Airflow
ODI
SSIS
BODI
Datastage

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave

Preferred Qualifications

Advanced Degree (MS) in engineering, technology, statistics, analytics, or finance.
Experience using BI tools (Tableau, QuickSight) to visualize data.
Experience developing, scaling, and governing global operations standards and infrastructure across matrixed organizations.
Experience with ETL tools such as Informatica, Airflow, ODI, SSIS, BODI, or Datastage.
Experience architecting and operating solutions built on AWS services including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2.
Experience in large-scale workforce, operations, or capacity planning functions.
Experience in data mining and handling large and complex datasets in a business context.
Experience in statistical analysis using tools such as R, SAS, or Matlab.

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