The cleaned title from the string AIML Architect-Dataflow,bigquery is AIML Architect .

The AIML Architect-Dataflow, BigQuery plays a crucial role within the organization by focusing on designing, implementing, and optimizing data architectures in Google Cloud's BigQuery environment. Your primary responsibility will involve combining advanced data analytics with artificial intelligence and machine learning techniques to create efficient data models that improve decision-making processes across various departments. Building data pipeline solutions that utilize BigQuery and Dataflow functionalities to ensure high performance, scalability, and resilience in data workflows will be key. Collaboration with data engineers, data scientists, and application developers is essential to align technical vision with business goals. Your expertise in cloud-native architectures will be instrumental in driving innovation, efficiency, and insights from vast datasets. The ideal candidate will have a strong background in data processing and AI/ML methodologies and be adept at translating complex technical requirements into scalable solutions that meet the organization's evolving needs. Responsibilities: - Design and architect data processing solutions using Google Cloud BigQuery and Dataflow. - Develop data pipeline frameworks supporting batch and real-time analytics. - Implement machine learning algorithms to extract insights from large datasets. - Optimize data storage and retrieval processes to enhance performance. - Collaborate with data scientists to build scalable models. - Ensure data quality and integrity throughout the data lifecycle. - Align data workflows with business objectives through collaboration with cross-functional teams. - Conduct technical evaluations of new tools and technologies. - Manage large-scale data migrations to cloud environments. - Document architecture designs and maintain technical specifications. - Provide mentorship to junior data engineers and analysts. - Stay updated with industry trends in cloud computing and data engineering. - Design and implement security best practices for data access and storage. - Monitor and troubleshoot data pipeline performance issues. - Conduct training sessions on BigQuery best practices for team members. Requirements: - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. - 5+ years of experience in data architecture and engineering. - Proficiency in Google Cloud Platform, specifically BigQuery and Dataflow. - Strong understanding of data modeling and ETL processes. - Experience implementing machine learning solutions in cloud environments. - Proficient in programming languages like Python, Java, or Scala. - Expertise in SQL and query optimization techniques. - Familiarity with big data workloads and distributed computing. - Knowledge of modern data processing frameworks and tools. - Strong analytical and problem-solving skills. - Excellent communication and team collaboration abilities. - Track record of managing comprehensive projects from inception to completion. - Ability to work in a fast-paced, agile environment. - Understanding of data governance, compliance, and security. - Experience with data visualization tools is a plus. - Certifications in Google Cloud or relevant technologies are advantageous.,