Data Engineer

This onsite Data Engineer role in Culver City offers a competitive annual compensation ranging from USD 132,100 to 178,800, along with a comprehensive benefits package. You will gain health coverage, 401(k) matching, paid time off, parental leave, sign-on payments, restricted stock units, and programs that support mental health, EAP, and flexible spending accounts. The role centers on Prime Video data infrastructure within Global Operations, emphasizing collaboration, governance, and scalable analytics.

As a Data Engineer, you will design, build, and scale data systems that enable reporting, analytics, and AI-enabled insights. The work includes shaping data models, governance practices, and automation to support forecasting, capacity planning, and self-service analytics.

Benefits

• Health insurance
• Employee Assistance Program (EAP)
• Mental health support
• Flexible Spending Accounts
• Adoption and surrogacy reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)

Responsibilities

• Design, implement, and maintain scalable data pipelines and ETL/ELT processes to ingest, transform, and deliver data that supports reporting and analytics needs
• Build the data platform to support agentic AI and Model Context Protocols, including structured pipelines, usage data capture, and systems enabling AI powered self-service analytics and reporting
• Develop and maintain data lakes, data warehouses, and APIs to provide reliable, performant access to clean, governed data while optimizing storage, query performance, and AWS costs
• Create logical data models that steer physical design, enabling BI and analytics teams to build self-service reporting on a solid foundation while supporting scalable forecasting and capacity planning
• Establish data quality programs with monitoring and alerts to ensure accuracy, completeness, and freshness; drive governance practices including lineage, documentation, and access controls
• Own the instrumentation strategy for key platforms to ensure comprehensive data capture across operational workflows
• Collaborate with 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
• At least three years of data engineering experience
• At least three years of experience with big data technologies such as Hadoop, Hive, Spark, or EMR
• Experience with data modeling, warehousing, and building ETL/ELT pipelines
• Four or more years of experience with one or more query languages (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
• Strong cross-team collaboration and effective written and verbal communication when interfacing with stakeholders, peers, and executives
• Familiarity with professional software engineering 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 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