Senior Data Platform Engineer

As an ideal candidate for this role, you should have 5-8 years of experience with a strong background in Python, specifically in monitoring, automation, and alerting. Additionally, hands-on experience operating Airbyte in production is a key requirement. Your expertise should also include running workloads on Kubernetes and a solid understanding of AWS services such as S3, IAM, and monitoring tools.

Key Responsibilities:

• Strong experience with Python for monitoring, automation, and alerting
• Hands-on experience operating Airbyte in a production environment
• Running workloads on Kubernetes
• Understanding and utilization of AWS services, especially S3, IAM, and monitoring tools
• Implementing data ingestion pipelines and familiarity with ETL/ELT concepts
• Knowledge of logging, metrics, and alerting systems
• Managing cost visibility and optimizing cloud infrastructure
• Proficiency with Git and operational best practices
• Familiarity with containerization using Docker is preferred
• Experience with infrastructure cost monitoring tools is an added advantage
• Preferred knowledge of data platform reliability or SRE practices

Qualifications Required:

• 5-8 years of relevant experience
• Strong proficiency in Python
• Hands-on experience with Airbyte
• Proficiency in Kubernetes
• Solid understanding of AWS services, especially S3, IAM, and monitoring tools
• Experience with data ingestion pipelines and ETL/ELT concepts
• Familiarity with logging, metrics, and alerting systems
• Ability to manage cost visibility and optimization for cloud infrastructure
• Proficiency with Git and operational best practices
• Familiarity with Docker containerization is preferred
• Experience with infrastructure cost monitoring tools is an added advantage
• Knowledge of data platform reliability or SRE practices is preferred As an ideal candidate for this role, you should have 5-8 years of experience with a strong background in Python, specifically in monitoring, automation, and alerting. Additionally, hands-on experience operating Airbyte in production is a key requirement. Your expertise should also include running workloads on Kubernetes and a solid understanding of AWS services such as S3, IAM, and monitoring tools.

Key Responsibilities:

• Strong experience with Python for monitoring, automation, and alerting
• Hands-on experience operating Airbyte in a production environment
• Running workloads on Kubernetes
• Understanding and utilization of AWS services, especially S3, IAM, and monitoring tools
• Implementing data ingestion pipelines and familiarity with ETL/ELT concepts
• Knowledge of logging, metrics, and alerting systems
• Managing cost visibility and optimizing cloud infrastructure
• Proficiency with Git and operational best practices
• Familiarity with containerization using Docker is preferred
• Experience with infrastructure cost monitoring tools is an added advantage
• Preferred knowledge of data platform reliability or SRE practices

Qualifications Required:

• 5-8 years of relevant experience
• Strong proficiency in Python
• Hands-on experience with Airbyte
• Proficiency in Kubernetes
• Solid understanding of AWS services, especially S3, IAM, and monitoring tools
• Experience with data ingestion pipelines and ETL/ELT concepts
• Familiarity with logging, metrics, and alerting systems
• Ability to manage cost visibility and optimization for cloud infrastructure
• Proficiency with Git and operational best practices
• Familiarity with Docker containerization is preferred
• Experience with infrastructure cost monitoring tools is an added advantage
• Knowledge of data platform reliability or SRE practices is preferred