Data Engineer

Stellantis•Auburn Hills, MI

About The Position

We are looking for a DevOps / Data Engineer to build and manage scalable cloud infrastructure, CI/CD pipelines, and data workflows on AWS. This role combines DevOps, automation, and data engineering, with exposure to modern data platforms like Databricks, to enable reliable application delivery and data-driven platforms. This role requires strong ownership, problem-solving skills, and the ability to work across DevOps, data, and engineering teams.

Requirements

Bachelor’s or master’s degree in computer science, engineering, or related field
3+ years' experience
Strong experience in AWS Cloud & DevOps
Strong programming skills in Python for automation and data processing
Hands-on with Terraform and AWS CDK
Experience with CI/CD tools (GitHub Actions, Bitbucket, Bamboo)
Experience with Docker, Kubernetes/OpenShift
Knowledge of data pipelines, ETL, and analytics workflows
Experience with monitoring and visualization tools such as Grafana
Familiarity with logging, monitoring, and incident management
Strong problem-solving and analytical skills
Good communication and stakeholder collaboration
Experience working in Agile/Scrum environments

Nice To Haves

Experience with Databricks or similar big data platforms
Experience with event-driven architecture (AWS Lambda)
Knowledge of Power BI or data visualization tools
Exposure to Generative AI / RAG / LLM concepts
Experience in enterprise or automotive data platforms
Familiarity with Terramate or similar IaC orchestration tools
Cloud or DevOps certifications (e.g., AWS Certified Solutions Architect, AWS Certified DevOps Engineer, Kubernetes certifications)

Responsibilities

Build and maintain CI/CD pipelines using GitHub Actions / Bitbucket Pipelines
Develop and manage Infrastructure as Code (IaC) using Terraform and AWS CDK
Manage and optimize AWS services (EC2, S3, Lambda, RDS, API Gateway)
Deploy and support containerized applications using Docker and Kubernetes/OpenShift
Develop and support data pipelines and ETL workflows using Python and SQL
Work with Databricks or similar data platforms for data processing and analytics
Implement DevSecOps practices, including SAST and secrets management (HashiCorp Vault)
Implement monitoring and observability solutions using tools like Grafana
Monitor systems, troubleshoot issues, and improve performance, reliability, and observability

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