Data Engineer III/Senior (AI and Gen AI)

Expeditors•Irving, MI

16h•$130,000 - $150,000•Onsite

About The Position

We are seeking a highly skilled and hands-on Data Engineer III or Senior Data Engineer to design, build, and operate enterprise-scale data pipelines, data products, and data platforms , with a strong emphasis on incorporating Generative AI capabilities into production systems. This is first and foremost a data engineering role . The successful candidate will own the development of reliable, scalable, and observable data systems that power analytics, applications, and operational workflows, while also integrating LLM-based and AI-enabled features where they add clear business value. This role sits within the engineering discipline and works closely with the architecture community . You will partner with data scientists, product teams, platform engineers, architects, and business stakeholders to ensure that AI capabilities are embedded within well-designed data systems , not built in isolation. This position supports the Americas geography under the Global Technology organization and contributes to initiatives that enhance operations across 70+ offices in multiple countries . A successful Data Engineer III / Senior Data Engineer : Builds and operates production-grade data pipelines, data platforms, and data products Incorporates AI and Generative AI capabilities into data systems in a pragmatic, maintainable way Designs systems that balance scalability, reliability, cost, security, and observability Raises the bar for engineering quality and operational excellence Acts as a technical leader and mentor , influencing design decisions and standards across teams

Requirements

Proven experience building and operating production-grade data pipelines and systems
Experience incorporating AI or Generative AI capabilities into data-driven systems
Experience with CI/CD, containerization, and modern DevOps practices
Ability to design reliable, observable, and secure data platforms
Strong proficiency in Python and SQL

Nice To Haves

Experience with Azure-native data and platform services
Familiarity with LLMs, embeddings, RAG architectures, and AI orchestration frameworks
Experience deploying systems with governance, security, and compliance requirements
Background in platform engineering or internal data platforms
Experience mentoring engineers or leading cross-team technical initiatives

Responsibilities

Design and implement scalable data ingestion, transformation, and serving pipelines
Build and operate data products and shared data services that support analytics and applications
Ensure data quality, lineage, reliability, and observability across systems
Manage dependencies and impacts across adjacent platforms and downstream consumers
Integrate Generative AI capabilities (LLMs, embeddings, RAG patterns, agentic workflows) into data pipelines, products, and services
Design AI-enabled components that align with enterprise-scale data and platform architectures
Ensure AI features meet governance, compliance, security, and observability requirements
Partner with data scientists to productionize AI models and experiments within data platforms
Design, deploy, and operate cloud-native data and AI systems on Azure
Implement Infrastructure as Code (e.g., Bicep, Terraform) for secure, repeatable environments
Build and maintain CI/CD pipelines supporting frequent, safe production releases
Contribute to engineering standards for data and cloud platforms
Own or share responsibility for the operational health of data and AI systems
Participate in on-call rotations and contribute to resilient, self-healing architectures
Optimize systems for performance, reliability, and cost at scale
Demonstrate strong incident response and operational decision-making
Lead or significantly contribute to technical designs for data and AI-enabled systems
Mentor engineers and reinforce data and engineering best practices
Partner with architects, managers, and stakeholders to align systems with business goals
Advocate for modern data engineering and AI platform patterns across teams