3 of 3 Permanent Databricks Jobs in Avon

data engineering, data integration and data modelling Expertise with cloud platforms (e.g. AWS, Azure, GCP) Expertise with modern cloud data platforms (e.g. Microsoft Fabric, Databricks) Expertise with multiple data analytics tools (e.g. Power BI) Deep understanding of data wareho using concepts, ETL/ELT pipelines and dimensional modelling Proficiency … Experience defining and enforcing data engineering standards, patterns, and reusable frameworks Professional certifications in relevant technologies (e.g. Microsoft Azure Data Engineer, AWS Data Analytics, Databricks Certified Professional Data Engineer) Skills Data Development Process Design, build and test data products that are complex or large scale Build and lead teams ...

deliver high-quality, secure, and scalable data solutions gaining exposure to multiple cloud platforms (AWS, Azure, OCI, GCP) and technologies such as Palantir Foundry, Databricks, Spark, and Airflow. Other times you will be working directly with the client, using your analytical and data skills to support their decision-making. … environment. Eligible for UK Security Clearance (or 5+ years UK residency . Desirable Skills & Exposure Familiarity with data lakes, warehouses, or streaming architectures (e.g. Databricks, Spark, Kafka). Experience with ETL tools, orchestration frameworks, or automation pipelines. Understanding of version control and CI/CD (e.g. GitHub, Azure DevOps). ...

ownership of the design, development, and maintenance of data models that underpin our enterprise data platform, with a particular focus on Databricks and the Nova platform. This role is critical in ensuring that our data assets are structured, governed, and optimised to support business intelligence, analytics, and reporting requirements. … data modelling lifecycle, from requirements gathering through to deployment and ongoing maintenance. Design, develop, and maintain logical and physical data models, primarily using Databricks and the Nova platform. Ensure data models are aligned with business requirements, data governance standards, and best practices. Collaborate with data engineers, architects, and business stakeholders ...