Sr 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