Employer description & source details
Design, build, and maintain cloud infrastructure and data platforms, primarily on GCP. Develop and maintain ETL/ELT data pipelines and orchestration workflows. Build and manage infrastructure using Terraform and infrastructure-as-code practices. Deploy and operate containerized workloads using Docker and Kubernetes. Develop data solutions using Python and SQL. Work with large-scale datasets using BigQuery, GCS, and other cloud-native services. Build and maintain CI/CD pipelines using GitHub Actions. Implement and maintain data lineage, metadata, and data dependency tracking across pipelines and datasets. Monitor infrastructure and pipeline health, troubleshoot failures, and optimize reliability, performance, and cost. Manage cloud permissions, secrets, service accounts, and infrastructure security. Support data consumers, software engineers, analysts, data scientists, and product teams. Improve automation, observability, deployment processes, and engineering standards across the platform. Use AI-assisted engineering tools effectively while applying appropriate review, testing, security, and operational controls. 3-5 years of hands-on experience in infrastructure engineering, data engineering, platform engineering, or a similar role. Strong experience with Google Cloud Platform, particularly BigQuery and Google Cloud Storage. Hands-on experience with Terraform or another infrastructure-as-code tool. Experience deploying and operating workloads using Kubernetes. Experience with an orchestration tool such as Airflow, Dagster, Prefect, or Flyte. Experience building and maintaining CI/CD pipelines, ideally using GitHub Actions. Strong database knowledge and experience working with cloud-based data infrastructure. Understanding of data lineage, metadata management, data quali
Extracted skills: python, sql, gcp, docker, kubernetes, terraform, security