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High brand, metro location, and broad mid-level data engineering skillset increase candidate competition.
Medium because core cloud data engineering skills transfer well, but telco network intelligence adds domain bias.
High due to mandatory cloud data engineering skills and specific tech stack requirements.
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Design, develop, and operate scalable cloud-native data platforms and pipelines mainly on GCP to support cloud engineering, operations, and network intelligence.
Develop and manage dashboards, reporting solutions, and automation using Python, APIs, AI/ML, and enterprise visualization tools like Tableau or Power BI.
Collaborate with global cross-functional teams to deliver data products aligned with business objectives, ensuring reliability, security, and compliance.
Hands-on experience with GCP, BigQuery, cloud data engineering, and data pipeline tools.
Proficiency in advanced SQL, Python scripting, and enterprise visualization tools (Tableau, Power BI, Grafana, or similar).
Knowledge of ETL processes, data warehousing, DevOps practices including CI/CD and Kubernetes, and cloud infrastructure management.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building end-to-end cloud data engineering solutions on GCP with a strong focus on automation and advanced analytics.
Capable of working effectively in agile environments with multiple global stakeholders and complex operational contexts.
Demonstrates ability to translate complex business and technical requirements into impactful data-driven solutions and insights.