4 of 4 Databricks Jobs in the North East

Cleared Databricks Data Engineer - Hybrid - Outside IR35 We are seeking a skilled Databricks Data Engineer to design, build, and optimize scalable data pipelines and analytics platforms. In this role, you will work closely with data scientists, analysts, and product teams to deliver reliable, high-performance data solutions using Databricks … modern cloud technologies. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Delta Lake Build and optimize ETL/ELT workflows for batch and streaming data Develop data models to support analytics, reporting, and machine learning use cases Ensure data quality, reliability, and performance across ...

create unified views to enhance performance and outcomes. Pipeline Development & Automation : Build, optimise, and automate scalable data pipelines using tools like Azure, Fabric, and Databricks; develop reusable components and templates. Governance, Quality & Security : Ensure data quality, governance, classification, retention, and robust security measures across the data lifecycle, supporting compliance … goals. Proficiency in the design and implementation of modern data architectures (ideally Azure/Microsoft Fabric/Data Factory) and modern data warehouse technologies (Databricks, Snowflake) Experience with database technologies such as RDBMS (SQL Server, Oracle) or NoSQL (MongoDB) Knowledge in Apache technologies such as Spark, Kafka and Airflow ...

Role: Data & ML Engineer Location: Newcastle Upon Tyne Levels: Senior Analyst, Specialist Experience Level: 3+ years Please Note: Due to the nature of client work you will be undertaking, you will need to be willing ...

data-driven decision-making at scale. Key Responsibilities Own and manage the product vision, roadmap, and backlog for data platform capabilities on AWS and Databricks Work closely with data engineers, architects, analysts, and stakeholders to define and prioritise features and enhancements Translate business requirements into clear user stories, acceptance criteria … platform stakeholders across the organisation Ensure data products are scalable, secure, cost-efficient, and aligned with best practices Drive adoption and value realisation of Databricks (e.g. data engineering, analytics, ML use cases) Collaborate with engineering teams to plan sprints, manage dependencies, and remove blockers Balance short-term delivery with long ...