Enterprise Architect – Data/AI
| Company | Toyota |
|---|---|
| Location | Plano, TX, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s Degree (or higher).
- Solid technology platform architecture experience driving highly scalable data solutions in a hybrid cloud environment (AWS preferred)
- Solid background in data modeling, cloud-based data solution, data visualization using technology like Tableau, Prometheus, Power BI, Graphana
- Solid knowledge of Data Governance and Data Risk practices.
- Solid knowledge of SQL and NoSQL datastores like MySQL, Oracle, MongoDB, DynamoDB, RDS.
- Solid knowledge of Streaming and Real-Time Stream Processing platforms like Kafka, RabbitMQ, Flink, Spark…
- Solid knowledge of Data Pipelines and Data Lakehouse solutions inclusive of Data Brick, Snowflake, Fabric, Iceberg…
- Experience in Data analysis and Data science toolset like Jupyter notebook, Python
- Know how to navigate the ethical AI practices and ensuring compliance with data protection regulations
- Practical experience in designing AI applications and knowledge of machine learning frameworks/platforms like AWS SageMaker, TensorFlow, PyTorch
- Experience partnering with engineers, architects and platform teams to drive and deliver end-to-end technical architecture & automated developer experiences.
- Well-versed in architecting solutions using CI/CD pipelines for full automation.
Responsibilities
- Lead and facilitate in-depth technology discussions and workshops across various teams, clearly articulating and presenting technology alternatives and recommendations to stakeholders at all levels.
- Stay up-to-date with industry trends and technologies in their fields to make sure our solutions are kept cutting-edge.
- Drive innovation in their field, conducting Proof of Concept in collaboration with other architects and engineers.
- Create and help in the adoption of relevant technology roadmaps, requirements, patterns, and practices for their respective area of focus to build best in class applications.
- Direct the creation of standards, re-usable components, and design patterns and propose solutions to meet business needs.
- Conduct training and coach teams on selected technology and adopted requirements.
- Maintain our Data Strategy to support modern Data and AI Products in collaboration with our Data Engineering and Data Science organization.
- Drive the creation of our next generation Data Platform to support real-time operational solutions as well as data analytical workloads.
- Provide technical leadership in creating our Machine Learning platform in collaboration with our platform team and Data Science team to support new AI technologies like GenAI.
- Ensure data governance and risk guardrails and policies are appropriately integrated into our data architecture.
Preferred Qualifications
-
No preferred qualifications provided.