KTek Resourcing
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with a contract length of "unknown", offering a pay rate of "unknown". Key skills include Python, FastAPI, Docker, Kubernetes, and experience with data platforms like Apache Spark.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 29, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte Metro
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🧠 - Skills detailed
#Data Pipeline #Deployment #Microservices #API (Application Programming Interface) #GitHub #Kubernetes #Scala #Docker #Data Engineering #FastAPI #Observability #Apache Spark #"ETL (Extract #Transform #Load)" #Spark (Apache Spark) #Python #Pytest
Role description
Role Overview:
We are hiring a Python Platform Engineer to build containerized API services that provide secure, scalable access to data platforms like Apache Spark. This is a platform engineering role focused on building reusable services—not just working on data pipelines.
Key Skills:
• Python, FastAPI
• Docker, Kubernetes
• CI/CD (GitHub Actions)
• API development / microservices
• Data platform exposure (Spark, ETL, pipelines)
Responsibilities:
• Build production-grade APIs and platform services
• Design scalable, containerized systems
• Implement async processing & job-based workflows
• Ensure testing, deployment, and observability
Good to Have:
• ARQ, Pytest
• Experience with platforms / internal frameworks
Role Overview:
We are hiring a Python Platform Engineer to build containerized API services that provide secure, scalable access to data platforms like Apache Spark. This is a platform engineering role focused on building reusable services—not just working on data pipelines.
Key Skills:
• Python, FastAPI
• Docker, Kubernetes
• CI/CD (GitHub Actions)
• API development / microservices
• Data platform exposure (Spark, ETL, pipelines)
Responsibilities:
• Build production-grade APIs and platform services
• Design scalable, containerized systems
• Implement async processing & job-based workflows
• Ensure testing, deployment, and observability
Good to Have:
• ARQ, Pytest
• Experience with platforms / internal frameworks
