Sr. GCP Data Engineering

As an experienced Data Engineer with over 10+ years of experience, you will be responsible for designing and implementing scalable, reliable, and efficient data pipelines and architectures across Google products and services. Your key responsibilities will include: - Developing and maintaining data models, schemas, and ontologies to support a variety of data sources and use cases. - Evaluating and recommending new data technologies and tools to improve infrastructure and capabilities. - Collaborating with product managers, engineers, and researchers to define data requirements and deliver robust technical solutions. - Building and optimizing batch and real-time data pipelines using Google Cloud Platform (GCP) services such as Dataflow, Dataproc, Pub/Sub, and Cloud Functions. - Implementing data quality checks and validation processes to ensure consistency and accuracy. - Designing and enforcing data governance policies to maintain data security and regulatory compliance. - Designing and managing scalable storage solutions with GCP services including BigQuery, Cloud Storage, and Spanner. - Optimizing data retrieval and storage strategies for performance and cost-efficiency. - Implementing data lifecycle management practices and archival strategies. Qualifications required for this role include: - 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. In addition to the above qualifications, the following are preferred qualifications: - Experience with data governance, data quality frameworks, and compliance. - Exposure to machine learning and data science workflows. - Experience with containerization and orchestration technologies such as Docker and Kubernetes. - Contributions to open-source projects or technical communities. - Google Cloud Professional Data Engineer certification.,