Azure Data Engineer with Machine Learning Expertise

Data Engineer with Machine Learning Expertise ( Azure )

Position Type : Full Time Position 
Experience : 5 +  yrs exp 
Job Location : Remote 

• Must have Skill : 
  Azure Cloud Services (e.g., Azure Data Factory, Azure Databricks, Azure Machine Learning, Azure Synapse Analytics).
  Python Programming and data science libraries (NumPy, Pandas, Scikit-learn, etc.).
  Data Engineering Concepts (ETL processes, data pipelines, data warehousing).
  Machine Learning Expertise.
  Database Skills (SQL and NoSQL, including MongoDB).

Role Overview

We are seeking a skilled and motivated Data Engineer with expertise in Machine Learning to join our team. This role will involve designing and implementing scalable data pipelines, developing machine learning models, and working with cutting-edge Azure tools and technologies to solve complex business problems.

Key Responsibilities

Data Engineering

• Design, develop, and maintain efficient and scalable data pipelines using Azure Data Factory, Azure Databricks, and other relevant tools.
• Extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, cloud storage) into Azure Data Lake Storage or Azure Synapse Analytics.
• Implement robust data quality checks and monitoring mechanisms to ensure data accuracy and integrity.
• Optimize data pipelines for enhanced performance and cost-efficiency.

Machine Learning and AI

• Develop and deploy machine learning models using Azure Machine Learning, including:
• AutoML for automated model development and experimentation.
• Python-based model development with frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Model deployment and operationalization using Azure Machine Learning services.
• Apply AI techniques (e.g., neural networks, deep learning) to address complex business challenges.
• Build and deploy predictive models to forecast trends and enable data-driven decision-making.

Mandatory Requirements

• Strong proficiency in Python programming and data science libraries (e.g., NumPy, Pandas, Scikit-learn).
• Hands-on experience with the Azure cloud platform, including Azure Data Factory, Azure Databricks, Azure Machine Learning, and Azure Synapse Analytics.
• Solid understanding of machine learning algorithms and techniques (e.g., regression, classification, clustering, neural networks).
• Knowledge of data engineering concepts, including data pipelines, ETL processes, and data warehousing.
• Experience with SQL and NoSQL databases (e.g., MongoDB).
• Strong problem-solving and analytical skills.

Good to Have

• Familiarity with CI/CD pipelines and DevOps practices.
• Experience managing and maintaining Azure infrastructure components, including virtual machines, storage accounts, and network configurations.
• Knowledge of Docker, Kubernetes, and other cloud-native tools and technologies.
• Experience implementing security best practices to safeguard sensitive data and ensure compliance with industry standards.
• Skills in monitoring and optimizing cloud resources for performance and cost-efficiency.

Interested in applying for this Role : Send your resume to Reshma@bramkas.com