Back
Metro mid-level role with common 3–6 year band and recognizable employer increases applicant competition.
Strong GCP/BigQuery and PySpark requirements make candidate background highly domain-specific and less transferable.
Many mandatory cloud, Big Data, and infra skills plus explicit 5.5+ years requirement.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, implement, and maintain scalable Big Data and cloud solutions using GCP, BigQuery, PySpark, Python, and Airflow.
Develop, optimize, and manage data workflows, pipelines, and high-volume SQL queries for analytics workloads.
Deploy and manage containerized applications with Docker and Kubernetes, implement CI/CD pipelines, and maintain cloud infrastructure via Terraform and GCP networking/security configurations.
5.5+ years of total work experience.
Strong expertise in Google BigQuery, Python, SQL, PySpark, GCP fundamentals, and Kubernetes.
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Hands-on experience with Apache Airflow, GCP serverless services (Cloud Functions, Cloud Run), Python API frameworks (preferably FastAPI), Docker, Kubernetes, CI/CD tools (GitLab CI/CD, Octopus Deploy), and Terraform.
Experienced in building and optimizing large-scale data processing systems and cloud-native applications on GCP.
Skilled in managing end-to-end data engineering workflows with orchestration and automation tools, ensuring reliability and scalability.
Proficient in containerization, infrastructure as code, and cloud security configurations indicating a strong operational and cross-team collaboration orientation.