- Building and maintaining our data infrastructure on the AWS cloud platform, with a specific focus on supporting AI model training, development, and deployment.

- This includes designing, developing, and implementing data pipelines, ensuring the secure and efficient flow of data for our AI models.

Data for AI :

- Design and implement data pipelines specifically tailored for AI training and model development.

- Partner with AI data scientists and engineers to understand their data needs and ensure efficient data access.

- Implement data pre-processing and feature engineering techniques for optimal model performance.

AWS expertise :

- Design,develop, and maintain data infrastructure on the AWS cloud platform, leveraging services like S3,Redshift, Glue, Lambda, and Kinesis.

- Build and maintain data lakes and warehouses optimized for AI workloads.

- Implement automated data transformations,cleansing, and validation processes to ensure data quality.

Coding proficiency :

- Write code using Python,SQL, and other relevant programming languages, with a focus on libraries and frameworks commonly used in AI (e.g., TensorFlow, PyTorch).

Automation and monitoring :

- Automate data pipelines using CI/CD tools and related techniques.

- Monitor and troubleshoot data pipelines for performance, reliability,and data quality issues.

- 5 to 8 years of experience as a Data Engineer or similar role,with a demonstrated experience in supporting data pipelines for AI applications and their data requirements.

- Proven experience with AWS services,including S3, Redshift, Glue, Lambda, and Kinesis.

- Strong experience with Python and SQL.

- Strong understanding of AI libraries and frameworks.

- Experience with data warehousing and data modeling concepts.

- Excellent problem-solving and analytical skills.

- Ability to work independently and as part of a collaborative team.

- Strong communication and collaboration skills