Junior Platform Data Engineer

Gemini Solutions

Gurugram District

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+

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Job summary

Gemini Solutions is seeking a Data Platform Engineer to design, build, and manage data pipelines using Apache Airflow, Python, and Kubernetes on a hybrid infrastructure. You will deploy Airflow on Kubernetes, design scalable pipelines, and orchestrate workflows across on-premises and AWS to enable seamless data movement.

Collaborate with data engineers, analysts, and DevOps to ensure reliable data flow, monitor and optimize performance, and apply CI/CD and IaC practices (Terraform) where

Qualifications

  • 3–6 years of experience in data engineering or platform engineering.
  • Hands-on experience with Apache Airflow and Python.
  • Solid understanding of Kubernetes and container orchestration.
  • Experience with hybrid infrastructure (on-premises + AWS).
  • Familiarity with CI/CD and infrastructure-as-code tools (Terraform) is a plus.

Responsibilities

  • Design, develop, and maintain scalable data pipelines with Airflow and Python.
  • Deploy, configure, and manage Airflow on Kubernetes.
  • Integrate and orchestrate workflows across hybrid infrastructure (on-premises + AWS).
  • Collaborate with data engineers, analysts, and DevOps for reliable data flow.
  • Monitor, troubleshoot, and optimize pipeline performance.

Skills

Apache Airflow
Python
Kubernetes
Hybrid infrastructure
CI/CD

Tools

Terraform
GitLab
Helm

Job description

  • We are seeking a talented Data Platform Engineer to design, build, and manage data pipelines leveraging Apache Airflow. In this role, you will work with Python-based DAGs, orchestrate workflows on Kubernetes and enable seamless integration across on-premises and AWS cloud environments.
POSITION RESPONSIBILITIES
  • Design, develop, and maintain scalable data pipelines using Apache Airflow and Python.
  • Deploy, configure, and manage Airflow on Kubernetes clusters.
  • Integrate and orchestrate workflows across hybrid infrastructure (on-premises and AWS).
  • Collaborate closely with data engineers, analysts, and DevOps teams to ensure reliable and efficient data flow.
  • Monitor, troubleshoot, and optimize pipeline performance, reliability, and scalability.
EXPERIENCE AND REQUIRED SKILL SETS
  • 3–6 years of experience in data engineering or platform engineering.
  • Strong hands-on expertise with Apache Airflow and Python.
  • Solid understanding of Kubernetes and container orchestration.
  • Proven experience working with hybrid infrastructure (on-premises + AWS).
  • Familiarity with CI/CD practices and infrastructure-as-code tools (e.g., Terraform) is a plus.
  • Strong problem-solving skills with the ability to work independently.
Nice to Have
  • Experience with Terraform.
  • Knowledge of networking concepts.
  • Familiarity with GitLab.
  • Experience using Helm for Kubernetes application management.
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