5 of 5 Permanent Databricks Jobs in Cambridgeshire

best practices for data governance and security. Required Skills & Experience 5–10 years in data engineering roles, ideally within consultancy environments. Strong proficiency in: Databricks (PySpark) Azure Data Factory (ADF) SQL (complex queries and optimisation) Azure Data Services (Data Lake, Synapse, etc.) Excellent communication and stakeholder management skills. Nice ...

LLMs and/or Agentic Systems, from development to production. Hands-on experience with LLM frameworks (e.g. langchain, langgraph, llamaindex, langsmith), AI platforms (e.g. Databricks, mlflow) and containerization solutions (e.g. Docker) is valued. Strong software engineering fundamentals and proficiency in Python are a must. Be creative, ambitious and curious. ...

academic and professional services communities to drive adoption. Desirable Experience with major cloud and AI stacks such as Azure OpenAI/OpenAI, Azure ML, Databricks, Kubernetes, and Docker. Familiarity with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms (e.g., event hubs, service … pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools (e.g., MLflow, Azure ML, Databricks, SageMaker or Vertex) plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility ...

work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you'll do Research, prototype, and deploy LLM use cases … tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain ...

collaborative environment that values continuous learning, professional development, and technical excellence. Key Responsibilities: Playing a key role in shaping the foundations of a Databricks-based lakehouse platform - designing how the catalogue is structured, defining core dimensions/facts, and ensuring the platform is discoverable and useful across the business. Writing … concise technical documentation. Adapting within a fast-evolving environment and contributing across the data remit wherever needed. About You: Have hands-on experience building Databricks lakehouse architectures and are excited by shaping foundational data infrastructure. Understand how to engineer data platforms for trust, scalability, and discoverability, not just produce pipelines. ...