Data Engineer, Healthcare

Inizio Partners Corp•Dallas, TX

About The Position

Develop and maintain end-to-end Data Engineering pipelines for deploying, monitoring, and scaling machine learning models. Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems. Optimize model deployment processes by leveraging containerization technologies such as Docker or Kubernetes . Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management. Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.

Requirements

Bachelor's degree in Computer Science or a related field; advanced degree preferred.
Minimum 7 years of experience working as Data Engineer or similar role within a data-driven organization.
Experience with data modelling and database design is mandatory.
Proficiency in Python developing data pipelines/scripts.
Strong experience with SQL and PySpark is essential
Familiarity with cloud platforms like AWS/Azure/GCP for building scalable infrastructure solutions is highly desirable
Experience with version control systems like Git/GitHub for managing code repositories
Excellent problem-solving skills with the ability to analyze complex technical issues related to Data model deployments.

Nice To Haves

Strong understanding of machine learning concepts and algorithms is good to have

Responsibilities

Develop and maintain end-to-end Data Engineering pipelines for deploying, monitoring, and scaling machine learning models.
Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless integration of ML models into production systems.
Optimize model deployment processes by leveraging containerization technologies such as Docker or Kubernetes .
Implement continuous integration/continuous deployment (CI/CD) practices for ML model development lifecycle management.
Work closely with cross-functional teams to troubleshoot issues related to model performance or data quality in production systems.