126 to 150 of 274 Apache Spark Jobs in the UK excluding London

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

Optimise data workflows for performance, cost efficiency, and maintainability using modern data-engineering tools and platforms (e.g., Azure Data Factory, AWS Data Pipeline, Databricks, Apache Spark). Support the integration of data into visualisation platforms and analytical environments (e.g., Power BI, ServiceNow). Ensure adherence to data governance ...