Data Platform Engineer

Saige Partners

United States

5 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

7 years minimum

Compensation

$113,000.0 - $158,000.0

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Airflow Data Analysis Application Frameworks Microsoft Azure Big Data BigQuery Cloud Storage Continuous Integration Information Engineering DevOps Data Flow Control

+18 more

Github Python (Programming Language) Systems Development Life Cycle Cloudera SQL Databases Enterprise Data Management Scripting Google Cloud Data Ingestion System Availability Build Server Data Layers AI Platforms Kubernetes Information Technology Deployment Automation Software Version Control Jenkins

Job description

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.

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.

Preferred

Google Cloud Platform 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.