AI & Data Engineer
Summary
Build and maintain scalable data pipelines and AI/ML platforms using AWS, Snowflake, and Databricks to support analytics and model delivery.
Responsibilities
- Design, develop, and maintain scalable data pipelines for ingestion,transformation, and delivery.
- Build and automate ETL/ELT workflows to improve efficiency, reliability,and scalability.
- Develop data solutions using AWS services such as S3, Glue, Redshift,EMR, Athena, and Lambda.
- Work with Data Scientists and business stakeholders to support analytics,reporting, and AI/ML initiatives.
- Implement monitoring, logging, and data quality processes to ensurereliable data delivery.
- Maintain data governance, security, and compliance with organisationalpolicies and relevant regulations.
- Contribute to CI/CD, Infrastructure-as-Code, and automation initiativesto improve engineering practices.
- Document data pipelines, architecture, and technical processes.
Requirements
- Minimium 5 years of experience in Data Engineering and modern cloud dataplatforms.
- Strong expertise across AWS, Azure, and/or GCP ecosystems.
- Extensive experience with Snowflake and Databricks.
- Strong Python engineering skills and software engineering fundamentals.
- Experience leading technical delivery workstreams and mentoringengineers.
- Experience designing and implementing AI and ML data platforms.
- Experience implementing model monitoring and observability capabilities.
- Strong stakeholder managementand communication skills.
- Ability to align technical solutions with business outcomes.