GCP Data Engineer

1 week ago

Bengaluru, India Pradeepit Consulting Services Full time

Job Description Responsibilities: - GCP Solution Architecture & Implementation: Implement and architect data solutions on Google Cloud Platform (GCP), leveraging its various components. - End-to-End Data Pipeline Development: Design and create end-to-end data pipelines using technologies like Apache Beam, Google Dataflow, or Apache Spark. - Data Ingestion & Transformation: Implement data pipelines to automate the ingestion, transformation, and augmentation of data sources, providing best practices for pipeline operations. - Data Technologies Proficiency: Work with Python, Hadoop, Spark, SQL, BigQuery, BigTable, Cloud Storage, Datastore, Spanner, Cloud SQL, and Machine Learning services. - Database Expertise: Demonstrate expertise in at least two of these technologies: Relational Databases, Analytical Databases, or NoSQL databases. - SQL Development & Data Mining: Possess expert knowledge in SQL development and experience in data mining (SQL, ETL, data warehouse, etc.) using complex datasets in a business environment. - Data Integration & Preparation: Build data integration and preparation tools using cloud technologies (like Snaplogic, Google Dataflow, Cloud Dataprep, Python, etc.). - Data Quality & Regulatory Compliance: Identify downstream implications of data loads/migration, considering aspects like data quality and regulatory compliance. - Scalable Data Solutions: Develop scalable data solutions that simplify user access to massive data, capable of adapting to a rapidly changing business environment. - Programming: Proficient in programming languages such as Java and Python. Required Skills: - GCP Data Engineering Expertise: Strong experience with GCP Data Engineering, including BigQuery, SQL, Cloud Composer/Python, Cloud Functions, Dataproc + PySpark, Python injection, Dataflow + Pub/Sub. - Expert knowledge of Google Cloud Platform; other cloud platforms are a plus. - Expert knowledge in SQL development. - Expertise in building data integration and preparation tools using cloud technologies (like Snaplogic, Google Dataflow, Cloud Dataprep, Python, etc.). - Proficiency with Apache Beam/Google Dataflow/Apache Spark in creating end-to-end data pipelines. - Experience in some of the following: Python, Hadoop, Spark, SQL, BigQuery, BigTable, Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning. - Proficiency in programming in Java, Python, etc. - Expertise in at least two of these technologies: Relational Databases, Analytical Databases, NoSQL databases. - Strong analytical and problem-solving skills. - Capability to work in a rapidly changing business environment. Certifications (Major Advantage): - Certified in Google Professional Data Engineer/Solution Architect.

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