Data Engineer
Amazon Quicksight
Analytics
AWS
Big Data
Bigdata
Business Intelligence
Cloud
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Governance
Data Integration
Data Lake
Data Pipeline
Data Platform
Data Processing
Data Security
Data Visualization
Data Warehouse
Database
ETL
Hadoop
Reporting and Analytics
SQL
Job Description
This on-site Data Engineer role in Culver City, CA offers a comprehensive compensation package and the opportunity to shape Prime Video data infrastructure for Global Operations. Salary ranges from USD 132,100 to 178,800 per year. The benefits package includes health insurance, an Employee Assistance Program (EAP), mental health support, flexible spending accounts, adoption and surrogacy reimbursement, 401(k) matching, paid time off, parental leave, sign-on payments, and restricted stock units (RSUs).
Responsibilities
- Design, develop, and maintain scalable, automated data pipelines and ETL/ELT processes that ingest, transform, and deliver data to support business reporting and analytics needs.
- Architect data infrastructure for agentic AI and Model Context Protocols (MCP) including structured pipelines, usage data capture, and systems that power AI-enabled self-service analytics and reporting.
- Build and maintain data lakes, data warehouses, and APIs ensuring reliable, performant access to clean, well-governed data. Optimize storage, queries, and AWS infrastructure costs.
- Create logical data models that drive physical design, enabling BI/analytics teams to build self-service reporting on a solid foundation. Support forecasting and capacity planning at scale.
- Establish data quality frameworks, monitoring, and alerting to ensure accuracy, completeness, and freshness. Drive governance best practices including lineage tracking, 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 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 (e.g., SQL, PL/SQL, DDL, HiveQL, SparkSQL, Scala)
- Experience with Python or another scripting language for data processing
- Knowledge of data schema design including normalization, relational models, and dimensional models
- Cross-team collaboration skills and effective written and verbal communication when interfacing with stakeholders, peers, and executives
- Knowledge of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews, source control, continuous deployments, 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
- AWS: S3, Redshift, SageMaker, Kinesis, Lambda, EC2
- Informatica, Airflow, ODI, SSIS, BODI, Datastage
Preferred Qualifications
- Advanced Degree (MS) in engineering, technology, statistics, analytics, or finance
- Experience using BI tools (e.g., 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 working with large-scale, complex datasets in a business environment
- Experience in statistical analysis using tools such as R, SAS, or Matlab