4 of 4 Apache Spark Jobs in Surrey

evolution of data architecture and help shape the organisations data engineering capabilities. Key Responsibilities Design, build and optimise scalable data pipelines using Databricks, Apache Spark and Python. Develop and maintain robust ELT processes to ingest, transform and integrate data from multiple sources. Contribute to the design and evolution … platform performance. Essential Skills & Experience Strong hands-on experience with Databricks . Proven experience designing, implementing and optimising data pipelines. Strong knowledge of Apache Spark and Python . Understanding of Lakehouse architecture and modern data engineering principles. At least five years experience across ELT, data engineering and data ...

Responsibilities: Design, build and enhance a secure, scalable and reliable Databricks platform Develop and maintain batch and real-time data pipelines using Databricks, Apache Spark and Delta Lake Contribute to platform architecture, engineering standards and best practices across the data estate Work with Product, Analytics and Data Science … continuous improvement across the engineering team Job Requirements: Significant experience building and supporting scalable, production-grade data platforms Strong hands-on expertise with Databricks, Apache Spark, Delta Lake, Python and SQL Good understanding of cloud-based data engineering, ideally within Microsoft Azure environments Experience with Infrastructure as Code ...

GenAI infrastructure and workflows Skills and experience: Passionfor building scalable, resilient cloud data platforms Strongexperience with Databricks or Snowflake on AWS ProvenPython skills, including Spark and Airflow expertise AdvancedSQL skills and end‐to‐end data modelling experience Experiencebuilding batch and real-time data integrations Hands-onCICD skills with ...

partner management and ability to influence across teams and organisations. Continuous learning and improvement mentality. Desired Experience with big data technologies (e.g. Hadoop, Hive, Spark). Experience with generative AI, LLMs, or retrieval‐augmented generation (RAG). Exposure to Agentic AI concepts, including autonomous agents, tool use, and orchestration ...