4 of 4 Contract Apache Spark Jobs in London

wider stakeholders. Technical Environment Experience with some of the following technologies would be beneficial: Python SQL Cloud platforms – AWS, Azure or GCP Databricks Apache Spark/PySpark Kafka/event-driven architectures Airflow dbt Git/GitHub CI/CD Infrastructure as Code Modern data platforms and distributed ...

engineers should be adept at Extract, Transform, Load (ETL) processes. This includes using frameworks such as the Medallion Architecture, as well as tools like Apache Airflow, Fivetran, Azure Data Factory, and Amazon Glue to automate data workflows and ensure data quality. Familiarity with cloud computing services, such … Cloud Platform, is increasingly important. Data engineers often leverage these platforms for scalable data storage and processing capabilities. Knowledge of big data frameworks like Apache Spark, Beam is crucial for handling large datasets and real-time data processing. Understanding data modelling techniques helps data engineers design efficient data ...

messaging architectures. Data Platforms & Cloud Technologies Hands-on experience with: Azure Data Lake Databricks Snowflake Delta Lake Azure Synapse Analytics/Microsoft Fabric Spark/PySpark Strong understanding of: Data Lake and Lakehouse architecture Hybrid cloud environments Enterprise integration patterns Modern data formats including Parquet, Avro, and ORC DevOps ...

Qlik). Knowledge of Python or R for advanced analytics and automation is highly desirable. Familiarity with cloud/big data platforms (Snowflake, Databricks, Spark) is preferred. Key Requirements Minimum 5+ years of hands-on experience in Data Analytics or Data Science (experience within Customer Success, Operations, or Digital ...