7 of 7 Permanent Apache Spark Jobs in West Yorkshire

will initially be for 6 months. It is also fully remote. Key Responsibilities • Design, develop, and maintain batch and streaming data pipelines using Databricks (Apache Spark) • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data • Implement Delta Lake architectures (Bronze/Silver/… Gold layers) • Integrate data from multiple sources (databases, APIs, event streams, files) • Optimize Spark jobs for performance, scalability, and cost • Manage data quality, validation, and monitoring • Collaborate with analytics and ML teams to support reporting and model development • Implement CI/CD, version control, and automated testing for data ...

Azure, or Google Cloud) including data lakes, warehouses, and lakehouse solutions. Transform and process structured and unstructured data using modern ETL/ELT frameworks (Apache Spark, Airflow, dbt). Collaborate closely with product managers, analysts, and software developers to ensure seamless integration and high-quality data availability. Develop ...

Experience building and deploying cloud data platforms Infrastructure-as-Code and CI/CD practices (GitHub, CodeBuild, pipelines) Strong coding experience in Python (Pandas), Apache Spark, and/or Apache Iceberg Expertise in SQL and advanced data manipulation and analysis Experience with data warehouse design and data ...

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 ...

DevOps, with the freedom to shape how GenAI and ML are used across the platform. Tech stack: Python PyTorch or TensorFlow scikit-learn Spark Kafka Databricks LangChain and RAG-based GenAI systems Cloud-native Azure environment Important Details: Fully remote across ...

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 ...

kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...