Data Engineer II

TL;DR

Data Engineer II (AWS): Build and optimize end-to-end data pipelines and high-quality datasets for Amazon Security’s Veritas service, with an accent on data governance, data quality automation, and mission-critical processing at extremely large scale. Focus on designing CI/CD data pipelines, leveraging AI/LLMs to automate redundant engineering work, and implementing big-data technologies while writing high-performing SQL queries.

Location: USA, WA, Seattle

Salary: $132,100–$178,800 annually

Company

Amazon Security (AmSec) builds foundational security data services for security investigations and operational security initiatives.

What you will do

• Develop and influence data strategy and data storage roadmap with partners.
• Lead data governance design: define schemas and build tools for efficient, confidential data sharing.
• Improve data quality and operations by automating workflows and building full CI/CD data pipelines.
• Build end-to-end ingestion and transformation pipelines across multiple data sources and systems.
• Use AI/LLM to automate manual and redundant data engineering tasks.
• Evaluate and implement big-data technologies (e.g., Redshift, Iceberg, Hive/EMR, Spark, SNS, SQS) for extremely large datasets.

Requirements

• 4+ years of data engineering experience.
• Experience with data modeling, data warehousing, and building ETL pipelines.
• 4+ years analyzing and interpreting data using Redshift, Oracle, and/or NoSQL technologies.
• Knowledge of professional software engineering best practices across the full SDLC (coding standards, architectures, code reviews, source control, continuous deployments, testing, operational excellence).
• Ability to write high-performing, optimized SQL queries.

Nice to have

• Experience with AWS services such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles/permissions.
• Experience with non-relational data stores (object storage, document/key-value stores, graph databases, column-family databases).
• Experience as a data engineer or related specialty with a track record working with large datasets.

Culture & Benefits

• Inclusive, learning-focused team culture with ongoing DEI events and knowledge sharing.
• Training and career growth resources to support continuous development.
• Work-life harmony with flexibility as part of the working culture.
• Comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave.
• Compensation includes sign-on payments and RSUs; final offer depends on experience, qualifications, and location.

Hiring process

• Interviews and evaluation of technical fit for data engineering responsibilities.
• Accommodation support available during application and hiring if needed.