Data Engineer, Robotics Delivery and Packaging Innovation

The Robotics Delivery and Packaging Innovation team at Amazon.com Services LLC is seeking a Data Engineer to design, build, and run end-to-end ETL/ELT pipelines and supporting infrastructure for a trusted “source of truth” data store and metrics that power warehouse automation and customer packaging.

Key Responsibilities

• Build and maintain reliable, scalable ETL/ELT pipelines using SQL, Python, and Spark to support automated reporting for warehouse automation and customer packaging.
• Collaborate with other technology teams to extract, transform, and load data from multiple source systems across warehouse automation and customer packaging domains.
• Apply data modeling and ETL/ELT best practices, using SQL and Redshift, and manage “source of truth” data stores.
• Implement batch and real-time processing approaches to keep pipelines performant.
• Execute data quality practices including validation, deduplication, PII handling, drift detection, and monitoring to ensure dependable downstream use.
• Design and enforce data security and access controls throughout the data lifecycle to protect sensitive operational and performance data.
• Model data and metadata for both ad-hoc and pre-built reporting, delivering high-quality datasets for Business Intelligence Engineers, Data Scientists, and customer reporting needs.
• Manage and optimize AWS cloud computing resources supporting the data infrastructure.
• Use AI-assisted development tools (such as Amazon Q and Kiro) to accelerate pipeline development, SQL work, and debugging, while validating generated outputs for correctness.
• Create extensible, maintainable designs with a long-term roadmap that supports future machine learning and GenAI use cases.
• Participate in strategic and tactical planning discussions.

Required Qualifications

• 1+ years of data engineering experience.
• 2+ years of experience analyzing and interpreting data, including Redshift, Oracle, and NoSQL.
• Bachelor’s degree in a quantitative or technical field such as computer science, engineering, or statistics.
• Knowledge of distributed systems as it applies to data storage and computing.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with one or more query languages (for example: SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).
• Experience with one or more scripting languages (for example: Python, KornShell).

Technologies Used

• SQL, Python, Spark
• Redshift, Oracle, NoSQL
• PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala, KornShell
• AWS, Amazon Q, Kiro
• Hadoop, Hive, EMR
• Informatica, ODI, SSIS, BODI, Datastage

Preferred Qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR.
• Experience with one or more ETL tools such as Informatica, ODI, SSIS, BODI, or Datastage.

Compensation and Location

Bellevue, WA (onsite). Salary range: USD 101,300 - 160,000 per year.

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD& D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave

A Day in the Life

In this role, you will own end-to-end data pipelines and infrastructure that provide the “source of truth” for warehouse automation and customer packaging metrics. You will design, build, and operate robust ETL/ELT solutions that integrate complex inputs from dozens of sources so teams across the Robotics Delivery and Packaging Innovation Organization can make decisions based on trusted datasets.

You will work closely with Business Intelligence Engineers, Data Scientists, Software Engineers, Product Managers, and Operations teams to turn raw requirements into scalable pipeline outputs. The work includes championing data quality and security so stakeholders can rely on the data while sensitive operational information remains protected throughout its lifecycle.