Data Engineer

• Design and develop scalable feature engineering pipelines for machine learning applications.

• Build and maintain batch scoring pipelines to support large-scale ML workloads.

• Develop, deploy, and maintain model inference services for both real-time and batch predictions.

• Design and build secure, scalable REST APIs for model serving and data integration.

• Deploy, monitor, and optimize machine learning models in production environments.

• Integrate ML services with upstream and downstream systems to enable seamless data flow.

• Ensure the performance, reliability, scalability, and security of APIs and data pipelines.

• Collaborate closely with Data Scientists, Backend Engineers, and Product teams to deliver end-to-end ML solutions.

• Troubleshoot production issues and continuously improve system performance and reliability.
   

What We're Looking For

Required Skills

• Strong proficiency in SQL.

• Hands-on experience with Apache Spark and Azure Databricks.

• Experience in data modeling, feature engineering, and building scalable data pipelines.

• Strong programming skills in Python.

• Experience developing REST APIs using FastAPI, Flask, or similar frameworks.

• Good understanding of API authentication, security, scalability, and performance optimization.

• Hands-on experience deploying and managing machine learning models in production.

• Familiarity with software engineering best practices, including version control, testing, and code quality.
   

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.

• Experience working in Agile software development environments.

• Exposure to cloud platforms such as AWS, Azure, or GCP.

• Strong analytical, debugging, and problem-solving skills.

  • Self-motivated with the ability to work independently and take ownership of deliverables.