7 of 7 Apache Jobs in the City of London

data engineering tasks. Experience with cloud platforms such as: AWS, Azure, Google Cloud Platform (GCP) Hands-on experience with data technologies such as: Apache Spark, Databricks, Kafka, Airflow, Snowflake, Hadoop ecosystems Experience designing and maintaining data warehouses and data lakes. Knowledge of DevOps and CI/CD tooling (e.g. ...

based solutions. Experience working with Cosmos DB SDKs in technologies such as .NET, Java, Python, or Node.js. Strong understanding of distributed computing concepts and Apache Spark architecture. Hands-on experience developing data pipelines using PySpark. Experience with Pytest and automated testing frameworks. Strong understanding of partitioning, indexing strategies ...

data into something they can actually use and act on. What you'll be doing: Designing and building performant data ingestion pipelines using Apache Spark, ideally within Azure Databricks Contributing to the platform's data modelling and architecture Building dashboards and semantic models, and presenting these directly to stakeholders ...

focus areas: Building scalable data pipelines using Apache Spark & Airflow Working within a cloud-based, containerised environment (Kubernetes) Contributing to a wider data platform modernisation programme Supporting both batch and streaming workloads Tech: Python, Java, Spark, Airflow, SQL, Cloud (AWS/Azure), Kubernetes (Kafka/streaming nice to have ...

Data Engineer Experience Level Required in Years: 10 - 15 years Mandatory Required Skills Hands-on experience with Quantexa platform/Decision Intelligence Strong in Apache Spark/PySpark Proficiency in Python/Scala Experience in ETL, Data Engineering, Data Warehousing Knowledge of entity resolution, graph analytics, link analysis Experience ...

preparation. Machine learning and statistical methods, including model validation. Data analytics and visualisation techniques. Processing large datasets using batch or streaming tools such as Apache Spark. Data acquisition and fusion approaches. Cloud platforms (ideally AWS) and cloud-based data science solutions. DataOps principles and practices. Structured and unstructured databases. ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. You'll also play a key role in pre-sales activities, solution design, and helping to drive strategic Databricks initiatives across … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience designing ...