Python developer software engineer developer

Job Description

Python Developer Software Engineer (Developer)

The Python Developer is responsible for:

Designing, developing, and deploying end-to-end data science solutions within the Microsoft Azure and Databricks environment. This role will involve working with large datasets stored in Azure Data Lake Storage (ADLS) Gen2 and Databricks, building and training machine learning models using Python and relevant libraries, and implementing automated pipelines for model deployment and operationalization. The ideal candidate will be a self-starter with a strong understanding of the data science lifecycle, capable of translating business problems into technical solutions and effectively collaborating with cross-functional teams. The candidate must hold an active Baseline security clearance prior to commencement.

Key Duties And Responsibilities

The Python Developer will be responsible for, but not limited to:

• Develop, test, and maintain Python-based applications, scripts, and tools.
• Develop and implement robust Python-based solutions to efficiently read, process, and transform large datasets from Azure Data Lake Storage (ADLS) Gen2, Synapse and Databricks environments, ensuring data quality and readiness for model development.
• Design, implement, and train machine learning models using relevant Python libraries (e.g., scikit-learn, TensorFlow, PyTorch, MLflow within Databricks) to address specific business problems, iterating on model architecture and hyperparameters to achieve optimal performance.
• Develop and implement automated pipelines and deployment strategies (e.g., using Databricks Model Serving, Azure Machine Learning, containerisation) to seamlessly integrate trained models into production environments, ensuring scalability and reliability.
• Design and build automated workflows using Python and Azure services (e.g., Azure Data Factory, Databricks Workflows) to streamline data ingestion, model training, evaluation, and deployment processes, ensuring efficiency and repeatability.
• Implement monitoring solutions to track model performance and data drift in production, perform regular model evaluation, and develop strategies for model retraining and maintenance to ensure continued accuracy and relevance.
• Effectively collaborate with data engineers, business analysts, and other stakeholders to understand business requirements, communicate technical findings, and contribute to the overall data science strategy.
• Adhere to coding best practices, including version control, code documentation, and testing, to ensure maintainable, scalable, and high-quality Python code.

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