Swan Software Solutions

Candidates should have hands-on experience building end-to-end Azure data and machine learning platforms, including most of the following:

Designing and operating ETL / ELT pipelines in Azure 
Experience with Azure Data Factory for orchestration 
Experience with Azure Databricks for large-scale data processing 
Experience using Azure Data Lake Storage as the core data platform 
Building data pipelines that feed machine learning model training 
Experience with Azure Machine Learning or equivalent ML training platforms 
Implementing feature engineering pipelines and dataset versioning 
Experience operationalizing models and integrating predictions into production systems 
Working with large datasets and high-throughput pipelines

AI / ML Pipeline Experience 
The candidate should have experience building systems where data pipelines directly support AI/ML workflows, including: 
Preparing training datasets from raw operational data 
Building repeatable model training pipelines 
Managing feature engineering workflows 
Supporting model retraining and lifecycle management 
Designing systems where trained models are consumed by applications or services 
Ensuring pipelines support scaling training workloads efficiently