Data Engineer (ML Ops) || 12+ Years Experience || Remote

Summary: The role of Data Engineer (ML Ops) requires a highly experienced candidate with over 12 years in IT, focusing on strong data engineering skills and hands-on expertise in Databricks. The position is remote and emphasizes the need for candidates with real-world MLOps implementation experience, particularly in building and supporting production AI/ML pipelines. The ideal candidate should be capable of working independently in a client-facing environment.

Key Responsibilities:

• Develop and maintain data pipelines and ETL processes.
• Implement and monitor AI/ML models in production environments.
• Utilize Databricks for data engineering tasks.
• Deploy and scale machine learning models.
• Work with cloud platforms such as AWS, Azure, or Google Cloud.
• Ensure CI/CD practices for ML workflows.
• Design and manage data lake/lakehouse architecture.

Key Skills:

• 12+ years of IT experience.
• Strong background in data engineering.
• Hands-on expertise in Databricks.
• Experience with AI/ML and MLOps.
• Proficiency in Spark/PySpark.
• Knowledge of cloud platforms (AWS/Azure/Google Cloud Platform).
• Experience with model deployment and monitoring.
• Familiarity with CI/CD for ML workflows.
• Understanding of data lake/lakehouse architecture.

Salary (Rate): £48

City: undetermined

Country: undetermined

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT