Data and AI Engineer

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

As a Strategic Cloud Data Engineer, you will guide customers on how to ingest, store, process, analyze, and explore/visualize data on the Google Cloud Platform. You will work on data migrations and modernization projects, and with customers to design large-scale data processing systems, develop data pipelines optimized for scaling, and troubleshoot potential platform/product challenges. You will have an in-depth understanding of data governance and security controls. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering teams to build and constantly drive excellence in our products.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

• Interact with stakeholders to translate complex customer requirements into recommendations for appropriate solution architectures and advisory services.
• Engage with technical leads, and partners to lead high velocity migration and modernisation to Google Cloud Platform (GCP).
• Design, migrate/build and operationalise data storage and processing infrastructure using Cloud native products.
• Develop and implement data quality and governance procedures to ensure the accuracy and reliability of data.
• Take various project requirements and organize them into clear goals and objectives, and create a work breakdown structure to manage internal and external stakeholders.

Minimum qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
• Experience in developing and troubleshooting data processing algorithms and software (e.g., Python, Java, Scala, Spark, Hadoop).
  
• Experience building machine learning or data science solutions.

Preferred qualifications:

• Experience in working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools, environments, and data structures.
• Experience in Big Data, information retrieval, data mining, or Machine Learning.
• Experience in building multi-tier, high availability applications with modern technologies such as NoSQL, MongoDB, SparkML, and TensorFlow.
• Understanding of database type, with the ability to write complex SQLs.
• Understanding of distributed data processing frameworks and modern age GCP analytical and transactional data stores like BigQuery, CloudSQL, AlloyDB etc.
• Understanding of core AI/ML concepts and frameworks like TensorFlow or PyTorch.