Data Architect: I (Junior)
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Job Description
Job Description
We are searching for a Data Architect: I (Junior) to join our team in Columbus, Ohio. This role will provide an opportunity to work in a dynamic and innovative environment, focusing on the design and implementation of MLOps solutions. The selected individual will collaborate closely with data scientists, product owners, and engineers to deliver data-driven solutions that enhance business outcomes.
Responsibilities:
Collaborate with data scientists and product owners to design MLOps solutions that translate business requirements into technical specifications and architectures.
Partner with MLOps engineers to ensure the solutions designed are efficiently implemented and aligned with best practices.
Act as a liaison between business users, product owners, and MLOps engineers to ensure seamless communication and alignment on project goals.
Utilize both proprietary and open-source MLOps tools to build flexible and scalable machine learning pipelines.
Lead the end-to-end productionization process, working from model training to deployment and monitoring in real-time or batch systems.
Design and maintain robust CI/CD pipelines for model deployment using various tools, ensuring smooth collaboration with development teams.
Design APIs for batch and real-time model inference, ensuring reliability and scalability in production.
Identify and implement relevant open-source tools to enhance the team s MLOps platform, ensuring long-term flexibility and efficiency.
Continuously update with the latest developments in MLOps, integrating new open-source tools to optimize workflows.
Encourage continuous learning and experimentation within the team to foster innovation in MLOps practices. Bachelor's degree in Computer Science, Information Systems, or a related field
Proficiency in SQL and Python programming languages
Experience with cloud technologies such as AWS
Familiarity with Linux operating system
Understanding of data engineering and best practices
Knowledge of Scrum or other agile development methodologies
Proven ability in designing, production, and deployment of database architectures
Experience with data integration and monitoring tools
Understanding of business requirement documents and ability to translate them into technical specifications
Proven ability to collaborate effectively with various stakeholders
Strong communication skills and ability to provide training where necessary
Knowledge of automation practices and optimization techniques
Familiarity with various data architecture frameworks
Demonstrated innovation in previous roles
Experience with R code is a plus.
Responsibilities:
Collaborate with data scientists and product owners to design MLOps solutions that translate business requirements into technical specifications and architectures.
Partner with MLOps engineers to ensure the solutions designed are efficiently implemented and aligned with best practices.
Act as a liaison between business users, product owners, and MLOps engineers to ensure seamless communication and alignment on project goals.
Utilize both proprietary and open-source MLOps tools to build flexible and scalable machine learning pipelines.
Lead the end-to-end productionization process, working from model training to deployment and monitoring in real-time or batch systems.
Design and maintain robust CI/CD pipelines for model deployment using various tools, ensuring smooth collaboration with development teams.
Design APIs for batch and real-time model inference, ensuring reliability and scalability in production.
Identify and implement relevant open-source tools to enhance the team s MLOps platform, ensuring long-term flexibility and efficiency.
Continuously update with the latest developments in MLOps, integrating new open-source tools to optimize workflows.
Encourage continuous learning and experimentation within the team to foster innovation in MLOps practices. Bachelor's degree in Computer Science, Information Systems, or a related field
Proficiency in SQL and Python programming languages
Experience with cloud technologies such as AWS
Familiarity with Linux operating system
Understanding of data engineering and best practices
Knowledge of Scrum or other agile development methodologies
Proven ability in designing, production, and deployment of database architectures
Experience with data integration and monitoring tools
Understanding of business requirement documents and ability to translate them into technical specifications
Proven ability to collaborate effectively with various stakeholders
Strong communication skills and ability to provide training where necessary
Knowledge of automation practices and optimization techniques
Familiarity with various data architecture frameworks
Demonstrated innovation in previous roles
Experience with R code is a plus.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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