Design, develop, and maintain scalable data pipelines using GCP services such as Cloud Storage, BigQuery, Composer, DataProc, and Pub / Sub.
Work with both SQL and NoSQL databases for data extraction, transformation, and analysis.
Develop and optimize Python scripts for data processing, automation, and workflow orchestration.
Implement and manage data lake architectures, ensuring proper governance, lifecycle management, and cost optimization.
Collaborate with cross-functional teams (data science, analytics, product, engineering) to deliver reliable, cloud-based data solutions.
Apply best practices in ETL processes, cloud data architecture, and data quality frameworks.
Required Skills :
Strong hands-on experience with GCP data services : BigQuery, Pub / Sub, DataProc, Composer, Cloud Storage.
Proficiency in Python for data processing and automation.
Strong understanding of ETL pipelines and data warehousing concepts.
Experience with SQL (query optimization, schema design) and exposure to NoSQL databases (e.g., MongoDB, Bigtable, Cassandra).
Knowledge of data lake design, governance, and lifecycle management.
Familiarity with CI / CD, version control (Git), and modern data workflows.
Good to Have :
Experience with streaming data pipelines.
Exposure to data modeling and metadata management.
Knowledge of data security and compliance best practices.
Google Cloud Professional Data Engineer Certification.
Education :
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
(ref : hirist.tech)
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Data Engineer Google Cloud Platform • Bangalore
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