GCP Data Engineer

As a GCP Data Engineer, you will be responsible for designing and implementing solutions on Google Cloud Platform (GCP) utilizing various GCP components. Your key responsibilities will include: - Implementing and architecting solutions on GCP using components such as BigQuery, SQL, Cloud Composer/Python, Cloud Functions, Dataproc with PySpark, Python Injection, Dataflow with PUB/SUB. - Experience with Apache Beam, Google Dataflow, and Apache Spark in creating end-to-end data pipelines. - Proficiency in Python, Hadoop, Spark, SQL, BigQuery, BigTable, Cloud Storage, Datastore, Spanner, Cloud SQL, and Machine Learning. - Programming expertise in Java, Python, and other relevant technologies. - Certified in Google Professional Data Engineer/Solution Architect would be a significant advantage. Qualifications required for this role include: - Minimum of 5 years of IT or professional services experience in IT delivery or large-scale IT analytics projects. - In-depth knowledge of Google Cloud Platform; familiarity with other cloud platforms is a plus. - Expertise in SQL development and building data integration tools using cloud technologies like Snaplogic, Google Dataflow, Cloud Dataprep, and Python. - Identifying downstream implications of data loads/migration and implementing data pipelines for automation, transformation, and augmentation of data sources. - Advanced SQL writing skills, experience in data mining, ETL processes, and using databases in a complex business environment. In addition to the above, you should be able to work effectively in a dynamic business environment and provide scalable data solutions for simplified user access to extensive datasets. As a GCP Data Engineer, you will be responsible for designing and implementing solutions on Google Cloud Platform (GCP) utilizing various GCP components. Your key responsibilities will include: - Implementing and architecting solutions on GCP using components such as BigQuery, SQL, Cloud Composer/Python, Cloud Functions, Dataproc with PySpark, Python Injection, Dataflow with PUB/SUB. - Experience with Apache Beam, Google Dataflow, and Apache Spark in creating end-to-end data pipelines. - Proficiency in Python, Hadoop, Spark, SQL, BigQuery, BigTable, Cloud Storage, Datastore, Spanner, Cloud SQL, and Machine Learning. - Programming expertise in Java, Python, and other relevant technologies. - Certified in Google Professional Data Engineer/Solution Architect would be a significant advantage. Qualifications required for this role include: - Minimum of 5 years of IT or professional services experience in IT delivery or large-scale IT analytics projects. - In-depth knowledge of Google Cloud Platform; familiarity with other cloud platforms is a plus. - Expertise in SQL development and building data integration tools using cloud technologies like Snaplogic, Google Dataflow, Cloud Dataprep, and Python. - Identifying downstream implications of data loads/migration and implementing data pipelines for automation, transformation, and augmentation of data sources. - Advanced SQL writing skills, experience in data mining, ETL processes, and using databases in a complex business environment. In addition to the above, you should be able to work effectively in a dynamic business environment and provide scalable data solutions for simplified user access to extensive datasets.