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Niche GCP BigQuery specialization and senior level reduces applicant density despite Infosys brand.
Deep GCP BigQuery/Dataflow expertise limits transferability across non-cloud or non-data backgrounds.
Explicit 8–12 years and mandatory GCP BigQuery/Dataflow/Airflow skills enforce high shortlisting strictness.
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Design, develop, and maintain enterprise-scale data engineering solutions on Google Cloud Platform (GCP).
Build and optimize scalable ETL/ELT pipelines using Dataflow, Apache Beam, BigQuery, and Cloud Composer for large-scale data processing and analytics.
Implement workflow orchestration, data modeling, and performance tuning across GCP services including BigQuery, Cloud Spanner, Pub/Sub, Cloud Storage, and Cloud Functions.
8 to 12 years of experience in Data Engineering, Big Data, and Cloud Data Platforms.
Strong hands-on experience with Google Cloud Platform (GCP) services including BigQuery, Dataflow, Apache Beam, Apache Airflow/Cloud Composer, Cloud Spanner, Pub/Sub, Cloud Storage, and Cloud Functions.
Proficient in Python and SQL programming for data pipeline development.
Work Experience Required: 8 to 12 years in relevant data engineering roles.
Experienced in designing and optimizing large-scale data warehouses and real-time data pipelines on GCP at enterprise scale.
Skilled in workflow orchestration and CI/CD DevOps practices enabling scalable and reliable cloud data solutions.
Collaborates effectively with architects, business stakeholders, and developers to deliver cloud-native data engineering solutions.