What youll be doing

• Designing and maintaining data pipelines optimized for ML/AI workloads including handling of large-scale unstructured and semi-structured data.
• Building feature pipelines and feature stores that ensure reusability and consistency of data used by machine learning models.
• Collaborating with Data Scientists and ML Engineers to understand data requirements for training validation and production deployment .
• Ensuring data quality lineage and governance meet standards required for AI/ML applications.
• Supporting MLOps practices by integrating data pipelines with model training monitoring and deployment workflows.
• Leveraging distributed processing frameworks (e.g. Spark Databricks Azure Synapse) for scalable ML data processing .

Qualifications :

What you bring

• 8 years of experience as a Data Engineer wo...