OverviewWe\'re looking for a skilled Data Analytics Engineer to help drive the evolution of our clients data platform. This role is ideal for someone who thrives on building scalable data solutions and is confident working with modern tools such as Azure Databricks, Apache Kafka, and Spark. In this role, you\'ll play a key part in designing, delivering, and optimising data pipelines and architectures. Your focus will be on enabling robust data ingestion and transformation to support both operational and analytical use cases. If you\'re passionate about data engineering and want to make a meaningful impact in a collaborative, fast-paced environment, we want to hear from youPermanentBasingstoke (Hybrid - x2 PW)Up to 70,000 + Excellent PackageRole and ResponsibilitiesDesigning and building scalable data pipelines using Apache Spark in Azure DatabricksDeveloping real-time and batch data ingestion workflows, ideally using Apache KafkaCollaborating with data scientists, analysts, and business stakeholders to build high-quality data productsSupporting the deployment and productionisation of machine learning pipelinesContributing to the ongoing development of a Lakehouse architectureWorking in an Agile/DevOps environment to continuously improve platform performance and reliabilityEssential Skills and ExperienceProven experience with Azure Databricks and Apache SparkWorking knowledge of Apache Kafka and real-time data streamingStrong proficiency in SQL and PythonFamiliarity with Azure Data Services and CI/CD pipelines in a DevOps environmentSolid understanding of data modelling techniques (e.g., Star Schema)Excellent problem-solving skills and a high attention to detailDesirableAzure Data Engineer certificationExperience working with unstructured data sources (e.g. voice)Exposure to Power BI for downstream reporting (desirable, but secondary to platform engineering skills)Previous experience in regulated industries #J-18808-Ljbffr