ML Data Engineer

This ML Data Engineer opportunity is built around they will support the customer analytics function by developing and deploying machine learning models and techniques to deliver value around our consumer (B2C) data. It would suit someone who can bring directed, innovative mindset who is comfortable supporting the data needs of multiple teams to the role.

Known job details

• Take the lead in building out our capability in this area with new models and recommender systems.
• Manage the infrastructure necessary for optimal ETL or ELT of data using Python , SQL , and Google Cloud Platform (GCP) big data technologies, such as BigQuery, Dataflow, Dataproc.
• Business Intelligence Enablement : Prepare and transform pipeline data to support downstream analytics and feed BI tools (DOMO), enabling data-driven decision-making across the org.
• Enhance Data System Functionality : Collaborate with the Data Team to continuously improve the functionality, flexibility, and performance of data systems and platforms.

Likely focus of the role

• They will support the customer analytics function by developing and deploying machine learning models and techniques to deliver value around our consumer (B2C) data.
• Ensure that data flows support various cross functional teams across the business.
• Maintaining robust, scalable, and efficient data pipeline architecture to support current and future business needs.

Requirements mentioned

• Big Data Engineering : Proven experience designing, building, and optimizing ‘big data’ pipelines, architectures, and datasets , enabling efficient data processing at scale.
• Relevant technical experience with the stack, platform, data, or support environment is important.