GCP Data Engineer

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 :

Certifications (Major Advantage) :

Skills Required

Google Cloud Platform, Sql Development, Python, Hadoop, Spark, Relational Databases