Job Description
- 10+ years of experience in design, architecture, implementation, and optimization of data engineering solutions over large volume (TB, PB scale) of data.
- Have expertise in designing and implementing end-to-end data architectures using Google Cloud Dataproc, including data ingestion pipelines, transformation logic, and data warehousing strategies to handle large-scale batch and real-time data processing.
- Proven expertise in GCP services including Dataproc, Dataflow, Cloud Storage, BigQuery, Cloud Composer, and Cloud Functions. Experience building scalable data lakes and pipelines.
- Strong hands-on experience processing large volumes of data; proficiency in PySpark, Python, Spark SQL, and automating workflows.
- Have good exposure to implementing robust data governance using Dataplex and security measures.
- Have proficiency in requirements analysis, solution design, development, testing, deployment, and ongoing support, including cloud migration projects for large-...
- Have expertise in designing and implementing end-to-end data architectures using Google Cloud Dataproc, including data ingestion pipelines, transformation logic, and data warehousing strategies to handle large-scale batch and real-time data processing.
- Proven expertise in GCP services including Dataproc, Dataflow, Cloud Storage, BigQuery, Cloud Composer, and Cloud Functions. Experience building scalable data lakes and pipelines.
- Strong hands-on experience processing large volumes of data; proficiency in PySpark, Python, Spark SQL, and automating workflows.
- Have good exposure to implementing robust data governance using Dataplex and security measures.
- Have proficiency in requirements analysis, solution design, development, testing, deployment, and ongoing support, including cloud migration projects for large-...
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