26 to 50 of 52 Apache Spark Jobs in the North of England

modern cloud engineering practices. Wherever you land, youll be working with some of the biggest datasets in the UK using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. The work you could be doing Design and deploy machine learning models for fraud detection, credit … risk, customer segmentation, and behavioural analytics using scalable frameworks like TensorFlow, PyTorch, and XGBoost. Engineer robust data pipelines and ML workflows using Apache Spark, Vertex AI, and CI/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing ...

experience in data engineering and 1+ experience as Lead Data Engineer Proven expertise with Microsoft Azure Strong proficiency in Databricks with hands-on Scala (Spark) and PySpark. Expertise in Databricks for large-scale data engineering and analytics workloads. Design and implement scalable data architectures using Databricks Unity Catalog, Delta … Lake, and Apache Spark Implement advanced Delta Lake features including time travel, vacuum operations, and Z-ordering. Desirable: certification in Databricks Data Engineer and/or Azure Data Engineer are a plus. ...

experience in data engineering and 1+ experience as Lead Data Engineer Proven expertise with Microsoft Azure Strong proficiency in Databricks with hands-on Scala (Spark) and PySpark. Expertise in Databricks for large-scale data engineering and analytics workloads. Design and implement scalable data architectures using Databricks Unity Catalog, Delta … Lake, and Apache Spark Implement advanced Delta Lake features including time travel, vacuum operations, and Z-ordering. Desirable: certification in Databricks Data Engineer and/or Azure Data Engineer are a plus. ...

experience in data engineering and 1+ experience as Lead Data Engineer Proven expertise with Microsoft Azure Strong proficiency in Databricks with hands-on Scala (Spark) and PySpark . Expertise in Databricks for large-scale data engineering and analytics workloads. Design and implement scalable data architectures using Databricks Unity Catalog … Delta Lake, and Apache Spark Implement advanced Delta Lake features including time travel, vacuum operations, and Z-ordering. Desirable: certification in Databricks Data Engineer and/or Azure Data Engineer are a plus. ...

organisation Supporting a move towards a product-aligned, hub-based operating model Technology Stack Cloud-first environment with Microsoft Azure Fabric Python, PyTorch SQL Apache Spark Azure Data Factory (ADF) Git What We’re Looking For 3–4 years’ experience in AI/ML engineering, data engineering ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

private/on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms). • Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar). • Experience designing scalable, distributed systems. • Familiarity with model lifecycle management and MLOps practices. • Proven ability to align AI initiatives to business outcomes ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...