AI & Data Engineer
Summary
Designs and maintains scalable data pipelines and AI/ML platforms using AWS, Snowflake, and Databricks to support analytics and machine learning initiatives.
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 management and communication skills.
· Ability to align technical solutions with business outcomes.