Title GCP BIG DATA ARCHITECT

You should have a strong understanding of the tech stack including GCP Services such as BigQuery, Cloud Dataflow, Pub/Sub, Dataproc, and Cloud Storage. Experience with Data Processing tools like Apache Beam (batch/stream), Apache Kafka, and Cloud Dataprep is crucial. Proficiency in programming languages like Python, Java/Scala, and SQL is required. Your expertise should extend to Orchestration tools like Apache Airflow (Cloud Composer) and Terraform, and Security aspects including IAM, Cloud Identity, and Cloud Security Command Center. Knowledge of Containerization using Docker and Kubernetes (GKE) is essential. Familiarity with Machine Learning platforms such as Google AI Platform, TensorFlow, and AutoML is expected. Candidates with certifications like Google Cloud Data Engineer and Cloud Architect are preferred. You should have a proven track record of designing scalable AI/ML systems in production, focusing on high-performance and cost-effective solutions. Strong experience with cloud platforms (Google Cloud, AWS, Azure) and cloud-native AI/ML services like Vertex AI and SageMaker is important. Your role will involve implementing MLOps practices, including model deployment, monitoring, retraining, and version control. Leadership skills are key to guide teams, mentor engineers, and collaborate effectively with cross-functional teams to achieve business objectives. A deep understanding of frameworks like TensorFlow, PyTorch, and Scikit-learn for designing, training, and deploying models is necessary. Experience with data engineering principles, scalable pipelines, and distributed systems (e.g., Apache Kafka, Spark, Kubernetes) is also required. Nice to have requirements include strong leadership and mentorship capabilities to guide teams towards best practices and high-quality deliverables. Excellent problem-solving skills focusing on designing efficient, high-performance systems are valued. Effective project management abilities are necessary to handle multiple initiatives and ensure timely delivery. Collaboration and teamwork are emphasized to foster a positive and productive work environment.,