Data Engineer, Prime Video - GSS Planning & Strategy
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Job Description
Data Engineer role within Prime Video Global Operations, onsite in Seattle, WA, offering USD 132,100 - 178,800 per year, focused on designing and scaling data infrastructure, pipelines, and AI-enabled analytics across marketing, finance, and cross-functional teams.
Responsibilities
- Build and maintain scalable, automated data pipelines and ETL/ELT processes that ingest, transform, and deliver data to support reporting and analytics needs.
- Design the data infrastructure to support agentic AI and Model Context Protocols (MCP), including structured pipelines, usage data capture, and systems for AI-powered self-service analytics and reporting.
- Develop and manage data lakes, data warehouses, and APIs to provide reliable, performant access to clean, well-governed data; optimize storage, query performance, and AWS cost efficiency.
- Model logical data structures that drive physical design, enabling BI and analytics teams to build self-service reporting on a solid foundation; assist with forecasting and capacity planning at scale.
- Implement data quality programs with monitoring and alerting to ensure accuracy, completeness, and freshness; promote governance practices including lineage tracking, documentation, and access controls.
- Lead the instrumentation strategy for key platforms to ensure comprehensive data capture across operational workflows.
- Collaborate across BI engineers, analysts, operations, science, and technology 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 of experience 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, or Scala).
- Experience with Python or another scripting language for data processing.
- Knowledge of data schema design including normalization, relational models, and dimensional models.
- Strong cross functional collaboration skills and effective written and verbal communication when interfacing with stakeholders, peers, and executives.
- Familiarity with professional software engineering practices across the full software development life cycle, including coding standards, code reviews, source control, continuous deployments, testing, and operational excellence.
- Experience using BI tools such as Tableau or 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
- MS degree in engineering, technology, statistics, analytics, or finance preferred.
- Experience using BI tools like Tableau or 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 working with large-scale, complex datasets in a business environment.
- Experience in statistical analysis using R, SAS, or Matlab.
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