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A Data Architecture Manager with an eye for AI. You will define and align the major types and sources of data necessary to support the business and determine how it is used, stored, managed and integrated within the organization’s IT systems and applications. You will need knowledge and understanding of the solution options for data science, data engineering, AI /ML engineering, edge analytics along with platforms, tools, frameworks, technologies, and vendors in those areas.
Work with the customer, users, technical architect, and RICEFW functional designers to define the data requirements and structure for the application.
Model and design modern application's data structure, storage, and integration.
Lead the database analysis, design, and build effort.
Work with the integration solution architects and designers to design the integration solution.
Ensure that the database designs fulfill the requirements, including data volume, frequency needs, and long-term data growth.
Work with the technical architects and RICEFW functional designers to understand the data conversion requirements fully and to design the conversion procedures and applications.
Review the database deliverables throughout development to ensure quality and traceability to requirements and adherence to all quality management plans and standards.
Work with other architects to ensure that all components work together to meet objectives and performance goals as defined in the requirements. Identify and communicate any cross-area or cross-release issues that may affect other areas of the project.
Ensure client data protection guidelines are followed for sensitive personal data in accordance to Accenture’s Client Data Protection program.
Here’s What You Need:
Minimum of 5 years technical solutions implementation, architecture design, evaluation and investigation in a cloud environment (specifically AWS, Azure and/or GCP), Hybrid, and/or On-Premise•
Minimum of 5 years of Client Management experience
Minimum of 5 years of professional experience in Solution/technical architecture in the cloud
Minimum of 5 years of experience in Big Data, Analytics, DevOps in the Cloud
Bonus Points If:
2 years of experience designing, documenting, and implementing analytics in end-to-end DevOps solutions applying concepts such as infrastructure-as-code, CI/CD, SAST/DAST, automated testing, push button deployments, etc.
You have hands-on experience with one or more of the following: Python, R, SAS, PySpark, Scala, Spark MLib, Jupyter, Spyder, MX Net, Databricks, Snowflake, MLFLow, ClearML, AWS Sagemaker, Azure Machine Learning, TensorFlow, Kubeflow, Airflow, Kubernetes
Experience in designing and deploying production models on a variety of cloud infrastructure, e.g. GPUs
Experience of deploying containerized models and ML pipelines using Docker, Kubernetes or equivalent technologies
Architected and successfully deployed end to end using data and machine learning technologies for business usage at an enterprise scale
You are Azure, AWS, or GCP solution architecture certified
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