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Tier-1 brand, metro location, and mid-level role increase applicant density.
Strong GCP and data engineering specialization limits cross-industry transferability.
Requires 5+ years, 4+ years GCP and many mandatory technologies, so strict filters.
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Lead design and development of enterprise-scale data pipelines and Data Lake platform evolution on Google Cloud Platform.
Build and optimize petabyte-scale, fault-tolerant data processing systems and real-time streaming architectures using GCP services and tools.
Provide technical leadership including code reviews, mentoring, knowledge sharing, and collaboration on cross-functional initiatives and team growth.
5+ years of data engineering experience with at least 4 years specifically on Google Cloud Platform.
Expertise with GCP tools including BigQuery, Cloud Dataflow, Composer, Cloud Storage, Pub/Sub, and Vertex AI.
Strong programming skills in Python and Java; proficiency with Apache Beam, Airflow, Kubernetes, Docker, Terraform, and CI/CD pipelines.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Experienced in delivering complex, enterprise-scale cloud-native data solutions with proven ability to translate business needs into scalable technical implementations.
Skilled in designing fault-tolerant, cost-efficient, and high-performance data architectures using advanced GCP and distributed computing technologies.
Effective technical mentor with aptitude for driving team capability through code quality standards, training programs, and collaborative project leadership.