Data Engineer Supply Chain Planning

Saige Partners•Eden Prairie, MN

13d

About The Position

Seeking an experienced Data Platform Engineer II to help build and improve enterprise data and analytics platforms in Google Cloud Platform (GCP). This role involves driving the roadmap and continuous improvement of data ingestion, orchestration, and platform tools, as well as building CI/CD, deployment automation, reusable frameworks, and self-service tools. The engineer will support and enhance Python-based data ingestion frameworks, establish SDLC, source control, deployment, and engineering standards, and improve platform reliability, monitoring, observability, and developer productivity. The role requires partnering with various teams including Data Engineering, Architecture, Infrastructure, Security, Governance, and Analytics, and evaluating new technologies to shape enterprise data platform strategy. Creating technical documentation, onboarding materials, and operational standards is also a key part of the position.

Requirements

Bachelor’s degree in Computer Science, Engineering, MIS, or related field.
7+ years of experience with enterprise data, analytics, cloud, DevOps, ingestion, orchestration, or related platforms.
Strong experience with CI/CD, automation, SDLC standards, and platform roadmaps.
Python, SQL, or scripting experience.
Experience building reusable tools, frameworks, and developer enablement solutions.
Strong communication, problem-solving, and cross-functional collaboration skills.
Ability to influence technical direction across teams.

Nice To Haves

GCP experience with BigQuery, Cloud Storage, Composer/Airflow, Pub/Sub, Dataflow, Dataproc, Kubernetes/GKE, Cloud Build, or similar services.
Experience with Azure DevOps, GitHub Actions, Jenkins, or similar CI/CD tools.
Experience with APIs, large-scale data ingestion, semantic layers, analytics, or AI platforms.
Experience supporting enterprise Data & Analytics organizations.

Responsibilities

Drive the roadmap and continuous improvement of data ingestion, orchestration, and platform tools.
Build CI/CD, deployment automation, reusable frameworks, and self-service tools.
Support and enhance Python-based data ingestion frameworks.
Establish SDLC, source control, deployment, and engineering standards.
Improve platform reliability, monitoring, observability, and developer productivity.
Partner with Data Engineering, Architecture, Infrastructure, Security, Governance, and Analytics teams.
Evaluate new technologies and help shape enterprise data platform strategy.
Create technical documentation, onboarding materials, and operational standards.