At least 5 years of experience in data engineering
Strong background on Azure Databricks and Scala/Python
Experience in handling unstructured data processing and transformation
Knowledge of MLOps fundamentals such as CI/CD, versioning, and monitoring
Requirements:
Build data pipelines using Scala/Python
Troubleshoot spark applications and resolve data pipeline issues
Build end-to-end data and ML solutions
Mentor junior staff members
Job description
Our client, a IT Services and Consulting company, is looking for a MLOps Engineer – Azure Databricks & MLflow for their Remote location.
Requirements:
At least 5 years of experience in a relevant discipline area is required. Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:
At least 5 years of experience in data engineering with a strong background on Azure Databricks and Scala/Python.
Experience in handling unstructured data processing and transformation with programming knowledge.
Hands on experience in building data pipelines using Scala/Python
Big data technologies such as Apache Spark, Structured Streaming, Advanced SQL, Databricks, Delta Lake, Azure/AWS
Strong analytical and problem-solving skills with the ability to troubleshoot spark applications and resolve data pipeline issues.
Familiarity with version control systems like Git, CICD pipelines.
Experience with Azure Databricks and MLflow
Good understanding of ML workflows, model development, and evaluation
Knowledge of MLOps fundamentals such as CI/CD, versioning, and monitoring
Ability to build end-to-end data and ML solutions
Exposure to production ML or AI systems
Understanding of data engineering and data modeling basics
Ability to work independently on loosely defined problems
