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Data Engineer with Airflow

Altitude Technology Solutions IncUnited States🇺🇸United StatesPosted 22 Jul 2026

Why This Role Stands Out

Elevate your career as a Data Engineer with Altitude Technology Solutions Inc., where you'll play a key role in architecting and supporting an enterprise-level Airflow platform, offering significant opportunities for skill development in cloud technologies and Kubernetes. This hybrid role is perfect for an experienced engineer eager to empower developers and drive impactful data solutions within a forward-thinking organization. Apply now to contribute to a cutting-edge data ecosystem and grow your expertise.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Position: Data Engineer with Airflow
Location: USA (Remote)
 
Justification
We are implementing Astronomer-backed Apache Airflow (Astro Private Cloud) as our enterprise orchestration platform on Azure Kubernetes Service (AKS). This platform provides a centralized, scalable scheduling and workflow orchestration layer for data pipelines and integrations across the organization.
We are seeking a hands-on engineer to support the platform with responsibilities spanning DAG development enablement and platform-level support. The ideal candidate should be comfortable working across Airflow (3.x+), Kubernetes, and cloud infrastructure, while enabling developers to efficiently adopt the platform.
 
Job Description
Experience - 4 - 6 years
 
Key Responsibilities
DAG Development & Developer Enablement
  • Design, develop, and optimize Airflow DAGs for enterprise use cases
  • Demonstrate strong experience with operators such as Python Operator, SQL Operators, API/HTTP Operators, Kubernetes Pod Operator, etc.
  • Apply advanced DAG patterns including dynamic DAGs, branching, sensors, retries, and error handling
  • Troubleshoot DAG failures, performance issues, and integration challenges
  • Enable orchestration of modern data workflows including DBT pipelines
  • Provide reusable templates, best practices, and onboarding support to drive self-service adoption Platform Operations & Kubernetes Support
  • Support Airflow platform deployed on AKS, covering scheduler, webserver/API, workers, and metadata services
  • Troubleshoot issues related to task execution, scheduling delays, and resource bottlenecks
  • Diagnose Kubernetes-level issues involving pods, networking, storage, and RBAC
  • Work with Azure services such as Key Vault, Storage, and networking
  • Support CI/CD pipelines for DAG and container-based deployments
  • Improve platform stability, monitoring, and alerting
 
Required Skills
  • Strong experience with Apache Airflow (3.x or later) in production environments
  • Proven experience in DAG development using operators and orchestration patterns
  • Working knowledge of Kubernetes (AKS preferred) to support Airflow runtime
  • Expert-level Python knowledge for building, debugging, and maintaining production-grade workflows and supporting libraries
  • Expertise in writing unit, integration, and DAG validation tests for Airflow workflows, including mocking operators, validating dependencies, and ensuring reliability in CI/CD pipelines
  • Experience with DBT and modern data pipelines
  • Experience with CI/CD tools (Git, Jenkins, Docker)
  • Familiarity with Azure or other cloud platforms
 
Preferred Skills
  • Experience with Astronomer/Astro Private Cloud
  • Exposure to data platforms such as Snowflake, and APIs
  • Experience with monitoring tools such as Splunk or Prometheus
  • Knowledge of secrets management using Azure Key Vault
 
Summary
This role is critical to ensuring reliable platform operations and scalable adoption of the Airflow-based orchestration platform. The ideal candidate combines strong Airflow expertise, Kubernetes knowledge, and hands-on development experience to support both platform stability and developer productivity.
 
 

Thanks & Regards

Kundan Mishra
Sr. Technical Recruiter
   

Skills

Docker
SQL
Snowflake
Splunk
Airflow
Apache
Astro
Azure
Git
HTTP
Jenkins
Kubernetes
Prometheus
Python
Vault
dbt

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