Data Engineer

Data Engineer role with Amazon.com Services LLC in Bellevue, WA (onsite); salary range USD 101,300 - 160,000 per year.

Responsibilities

• Design and implement robust ETL/ELT pipelines using AWS big data technologies to support the Amazon Air data warehouse.
• Create scalable data integration solutions that translate complex business requirements into actionable insights.
• Develop and maintain high‑performance data pipelines that underpin critical business intelligence capabilities.
• Proactively identify and resolve data infrastructure challenges to improve reliability and uptime.
• Collaborate with cross‑functional teams to enable data driven decision making across the organization.
• Contribute to the development and maintenance of AIR's GenAI infrastructure and data foundations.
• Architect data architectures that support generative AI applications and LLM workflows.
• Leverage GenAI tools such as Amazon Q and coding assistants to accelerate development and testing.

Requirements

• 2+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with one or more query languages: SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala.
• Experience with one or more scripting languages: Python, KornShell.
• Familiarity with leveraging GenAI/LLM tools to improve development productivity.

Technologies

• SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala, Python, KornShell
• Hadoop, Apache Spark, Informatica, ODI, SSIS, BODI, Datastage
• Amazon Redshift, Amazon S3, AWS Glue, AWS EMR, AWS Kinesis, AWS FireHose, AWS Lambda, IAM
• Amazon Q, GenAI tools

Benefits

• Health insurance (medical, dental, vision, prescription), Basic Life & AD&D insurance with 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
• Sign-on payments
• Restricted stock units (RSUs)

Preferred Qualifications

• Experience as a data engineer or related specialty with a track record of manipulating, processing, and extracting value from large datasets.
• Experience with big data processing technology (Hadoop or Apache Spark), data warehouse architecture, infrastructure components, ETL, and reporting/analytic tools.
• Knowledge of basic data schema design, including normalization and the relational versus dimensional models.
• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
• Experience with ETL tools such as Informatica, ODI, SSIS, BODI, Datastage, etc.