Google Cloud Data Engineering

You will be responsible for designing and implementing scalable, reliable, and efficient data pipelines and architectures across Google products and services. Your role will involve developing and maintaining data models, schemas, and ontologies to support various data sources and use cases. You will evaluate and recommend new data technologies and tools to enhance infrastructure and capabilities. Collaboration with product managers, engineers, and researchers to define data requirements and deliver technical solutions will be a key aspect of your responsibilities. Building and optimizing batch and real-time data pipelines using Google Cloud Platform (GCP) services like Dataflow, Dataproc, Pub/Sub, and Cloud Functions will also fall under your purview. Additionally, you will implement data quality checks and validation processes to ensure consistency and accuracy, as well as design and enforce data governance policies for data security and regulatory compliance. Managing scalable storage solutions with GCP services such as BigQuery, Cloud Storage, and Spanner, and optimizing data retrieval and storage strategies for performance and cost-efficiency will be part of your day-to-day tasks. Implementing data lifecycle management practices and archival strategies will also be crucial to your role. - Design and implement scalable, reliable, and efficient data pipelines and architectures. - Develop and maintain data models, schemas, and ontologies. - Evaluate and recommend new data technologies and tools. - Collaborate with cross-functional teams to define data requirements and deliver technical solutions. - Build and optimize batch and real-time data pipelines using GCP services. - Implement data quality checks and validation processes. - Design and enforce data governance policies. - Manage scalable storage solutions with GCP services. - Optimize data retrieval and storage strategies. - Implement data lifecycle management practices and archival strategies. - Bachelors or Masters degree in Computer Science, Engineering, or a related field. - 8+ years of experience in data engineering or a related discipline. - Strong knowledge of data warehousing, data modeling, and ETL development. - Proven expertise in designing and implementing large-scale data architectures and pipelines. - Proficiency in SQL and at least one programming language such as Python or Java. - Hands-on experience with GCP services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage. - Familiarity with open-source data tools like Hadoop, Spark, and Kafka. - Excellent communication and collaboration skills. (Note: No additional details about the company were mentioned in the job description),