Posted 08 July, 2026
Data Engineer
Diverse Lynx
Bengaluru,560001
Full Time
Reference: 365_569689_26-01080
Data Platform Engineer (Airflow / Azure / AKS)
Role Overview
We are seeking a Data Platform Engineer to join the Data Platform Engineering – Central Services team. The role focuses on the design, implementation and operation of a modern, cloud-based data platform supporting enterprise-scale data workloads.
The successful candidate will contribute to workflow orchestration, distributed data processing and platform engineering activities, with a strong emphasis on Airflow, Python development and Azure-based infrastructure.
Key Responsibilities
Required Skills and Experience
Preferred Skills
Technology Environment
The team operates a cloud-native data platform leveraging Airflow for workflow orchestration, Azure cloud services and Kubernetes-based deployments. The platform supports event-driven data processing and is continuously evolving to meet enterprise requirements.
About the Team
The Data Platform Engineering – Central Services team is responsible for building and operating shared platform capabilities that enable data-driven use cases across multiple domains. The team focuses on scalability, reliability and standardization, supporting internal consumers with robust and reusable data services.
Candidate Profile
The ideal candidate is a strong software engineer with a background in data platform engineering. They are comfortable working in distributed, cloud-native environments and have a proactive approach to problem solving. The candidate should demonstrate ownership, collaboration and a commitment to engineering excellence.
Role Overview
We are seeking a Data Platform Engineer to join the Data Platform Engineering – Central Services team. The role focuses on the design, implementation and operation of a modern, cloud-based data platform supporting enterprise-scale data workloads.
The successful candidate will contribute to workflow orchestration, distributed data processing and platform engineering activities, with a strong emphasis on Airflow, Python development and Azure-based infrastructure.
- Design, develop and maintain data workflows using Airflow, including DAG design, optimization and operational support
- Build scalable and reliable orchestration solutions for data pipelines
- Deploy, configure and operate Airflow on Azure, including Kubernetes-based environments (AKS)
- Develop and maintain production-grade code in Python
- Contribute to the design and evolution of a cloud-native data platform on Azure
- Implement and support event-driven data processing patterns and services
- Collaborate with data engineers, platform engineers and stakeholders to enable self-service data capabilities
- Ensure platform reliability through monitoring, logging and automation practices
- Contribute to the adoption of Data Mesh principles and platform engineering best practices
- Strong hands-on experience with Airflow, including DAG development and orchestration of complex workflows
- Solid programming skills in Python, with experience in building production systems
- Proven experience deploying and operating Airflow in Azure environments
- Practical experience with Kubernetes, preferably AKS, including deployment, scaling and troubleshooting
- Experience with event-driven architectures and distributed systems
- Familiarity with Data Mesh concepts such as domain ownership and data as a product
- Knowledge of Azure data services (for example Databricks, ADLS, messaging services)
- Experience with CI/CD pipelines and DevOps practices (e.g. GitLab CI/CD, Azure DevOps)
- Exposure to platform engineering or internal developer platforms
The team operates a cloud-native data platform leveraging Airflow for workflow orchestration, Azure cloud services and Kubernetes-based deployments. The platform supports event-driven data processing and is continuously evolving to meet enterprise requirements.
The Data Platform Engineering – Central Services team is responsible for building and operating shared platform capabilities that enable data-driven use cases across multiple domains. The team focuses on scalability, reliability and standardization, supporting internal consumers with robust and reusable data services.
The ideal candidate is a strong software engineer with a background in data platform engineering. They are comfortable working in distributed, cloud-native environments and have a proactive approach to problem solving. The candidate should demonstrate ownership, collaboration and a commitment to engineering excellence.
