Data Platform Engineer
Summary
Design and build scalable infrastructure for training and deploying generative AI models, optimizing performance and cost while collaborating with cross-functional teams.
About The Role
As a Data Platform Engineer, you will design and deliver scalable infrastructure that supports the training and deployment of generative AI models. This role plays a key part in enabling data-driven innovation by ensuring high-performance, reliable, and cost-efficient platforms. You will collaborate with cross-functional teams to build solutions that drive business impact and accelerate AI adoption.
Key Responsibilities
Design, build, and implement infrastructure to support large-scale training and inference of generative AI models
Optimize platform performance, scalability, and cost efficiency across data and AI workloads
Evaluate infrastructure technologies and vendors, providing recommendations aligned with business needs
Develop and maintain observability, monitoring, and operational controls for data platforms
Collaborate with engineering, analytics, and product teams to deliver robust and scalable AI solutions
Support continuous improvement of platform architecture and engineering practices
Contribute to technical discussions and problem-solving initiatives across teams
Build expertise in data platforms and AI infrastructure through hands-on experience and learning
Required Qualifications
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
Minimum 1 year of relevant experience in data engineering, platform engineering, or similar roles
Intermediate proficiency in Python, with hands-on experience using the Pandas library
Intermediate proficiency in Tableau or similar data visualization tools
Understanding of data processing, data pipelines, and large-scale data systems
Strong analytical and problem-solving skills with attention to detail
Ability to work independently and collaboratively in a team environment
Preferred Qualifications (Optional)
Basic knowledge of data architecture and database design principles
Familiarity with platform engineering concepts and cloud infrastructure
Exposure to technology architecture planning or roadmap development
Interest in generative AI technologies and their infrastructure requirements
As a Data Platform Engineer, you will design and deliver scalable infrastructure that supports the training and deployment of generative AI models. This role plays a key part in enabling data-driven innovation by ensuring high-performance, reliable, and cost-efficient platforms. You will collaborate with cross-functional teams to build solutions that drive business impact and accelerate AI adoption.
Key Responsibilities
Design, build, and implement infrastructure to support large-scale training and inference of generative AI models
Optimize platform performance, scalability, and cost efficiency across data and AI workloads
Evaluate infrastructure technologies and vendors, providing recommendations aligned with business needs
Develop and maintain observability, monitoring, and operational controls for data platforms
Collaborate with engineering, analytics, and product teams to deliver robust and scalable AI solutions
Support continuous improvement of platform architecture and engineering practices
Contribute to technical discussions and problem-solving initiatives across teams
Build expertise in data platforms and AI infrastructure through hands-on experience and learning
Required Qualifications
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
Minimum 1 year of relevant experience in data engineering, platform engineering, or similar roles
Intermediate proficiency in Python, with hands-on experience using the Pandas library
Intermediate proficiency in Tableau or similar data visualization tools
Understanding of data processing, data pipelines, and large-scale data systems
Strong analytical and problem-solving skills with attention to detail
Ability to work independently and collaboratively in a team environment
Preferred Qualifications (Optional)
Basic knowledge of data architecture and database design principles
Familiarity with platform engineering concepts and cloud infrastructure
Exposure to technology architecture planning or roadmap development
Interest in generative AI technologies and their infrastructure requirements