6 of 6 Permanent Databricks Jobs in the City of London

such as MongoDB or Cassandra Erwin Data Modeler, ER/Studio or similar modelling tools TOAD or equivalent SQL development tools Azure Data Factory, Databricks or other modern data platforms Git, Azure DevOps or similar version control tools Power BI or other BI platforms PL/ ...

implementing complex data-matching, reconciliation, and entity-resolution solutions across multiple data sources Distributed computing for data intensive work such as Spark and Databricks Cloud platforms including AWS, Azure and GCP Orchestration tools like Airflow Modern DevOps practices including version control, CI/CD, and infrastructure as code using Terraform ...

Responsibilities Develop and maintain scalable data pipelines using Azure Data Factory. Build and manage ETL processes using SQL and Python. Work with Azure Databricks and Azure SQL/SQL Server to process and manage large datasets. Design and implement data models using Kimball, 3NF and dimensional modelling approaches. Develop metadata … security throughout the data lifecycle. Experience Required Strong commercial experience working within Azure data environments. Hands-on experience with Azure Data Factory, Azure Databricks and Azure SQL/SQL Server. Strong SQL and Python skills. Previous experience working within Financial Services environments (Banks/Insurance/FinTech) Good understanding ...

frameworks. Excellent understanding of statistics, machine learning methodologies, and model evaluation. Experience delivering AI solutions from proof-of-concept through to production. Exposure to Databricks, MLflow, Spark, or similar cloud-based data platforms. Ability to influence senior stakeholders and lead technical strategy Desirable Experience Experience building multi-agent AI systems ...

experience with vector databases and semantic search pipeline design. Experience with Model Context Protocol (MCP). Experience with large-scale data platforms such as Databricks and search engines such as Elasticsearch, in an analytical or AI feature engineering context. Demonstrated ability to design enterprise-grade AI systems with strong ...

with monitoring and observability tools (Grafana, Splunk) and diagnostics platforms (New Relic, Dynatrace). Understanding of containerisation technologies (Docker, Kubernetes) and big data platforms (Databricks). Ability to analyse complex performance issues and provide actionable recommendations. Strong scripting skills (e.g., Python, JavaScript) for test automation and data analysis. Knowledge ...