276 to 300 of 516 Kafka Jobs in England

etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. 7. Ability More ❯

etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. 7. Ability More ❯

etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. 7. Ability More ❯

etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. 7. Ability More ❯

etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. 7. Ability More ❯

Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred -eg- Azure Data Engineer Associate. Advantageous skills: Azure Event Hubs, Kafka, data visualisation tools, Power BI, Tableau, Azure DevOps, Docker, Kubernetes, Jenkins. More ❯

collaborating with cross functional teams Strong Background and experience in Data Ingestions, Transformation, Modeling and Performance tuning. Should have experience in designing and developing dashboards Strong Knowledge in Hadoop, Kafka, SQL/NoSQL Should have experience in creating roadmap to improve platform Observability Experience in leading mid-scale teams with strong communication skills Experience in Machine Learning and GCP More ❯

collaborating with cross functional teams Strong Background and experience in Data Ingestions, Transformation, Modeling and Performance tuning. Should have experience in designing and developing dashboards Strong Knowledge in Hadoop, Kafka, SQL/NoSQL Should have experience in creating roadmap to improve platform Observability Experience in leading mid-scale teams with strong communication skills Experience in Machine Learning and GCP More ❯

collaborating with cross functional teams Strong Background and experience in Data Ingestions, Transformation, Modeling and Performance tuning. Should have experience in designing and developing dashboards Strong Knowledge in Hadoop, Kafka, SQL/NoSQL Should have experience in creating roadmap to improve platform Observability Experience in leading mid-scale teams with strong communication skills Experience in Machine Learning and GCP More ❯

collaborating with cross functional teams Strong Background and experience in Data Ingestions, Transformation, Modeling and Performance tuning. Should have experience in designing and developing dashboards Strong Knowledge in Hadoop, Kafka, SQL/NoSQL Should have experience in creating roadmap to improve platform Observability Experience in leading mid-scale teams with strong communication skills Experience in Machine Learning and GCP More ❯

collaborating with cross functional teams Strong Background and experience in Data Ingestions, Transformation, Modeling and Performance tuning. Should have experience in designing and developing dashboards Strong Knowledge in Hadoop, Kafka, SQL/NoSQL Should have experience in creating roadmap to improve platform Observability Experience in leading mid-scale teams with strong communication skills Experience in Machine Learning and GCP More ❯

Data implementation projects Experience in the definition of Big Data architecture with different tools and environments: Cloud (AWS, Azure and GCP), Cloudera, No-sql databases (Cassandra, Mongo DB), ELK, Kafka, Snowflake, etc. Past experience in Data Engineering and data quality tools (Informatica, Talend, etc.) Previous involvement in working in a Multilanguage and multicultural environment Proactive, tech passionate and highly More ❯

E-commerce and B2B platforms, with exposure to ERP, CRM, Product, Data, and Supply Chain systems. Knowledge of modern platforms and technologies such as: Cloud: AWS, Azure Data: Snowflake, Kafka, databases Customer Platforms: Adobe Commerce, Salesforce, Informatica, Treasure Data Engineering: Java, Node.js, React, GraphQL, containers, Terraform Integration: MuleSoft, SAP IS, Apollo GraphQL, Kong Minorities, women, LGBTQ+ candidates, and individuals More ❯

Data implementation projects Experience in the definition of Big Data architecture with different tools and environments: Cloud (AWS, Azure and GCP), Cloudera, No-sql databases (Cassandra, Mongo DB), ELK, Kafka, Snowflake, etc. Past experience in Data Engineering and data quality tools (Informatica, Talend, etc.) Previous involvement in working in a Multilanguage and multicultural environment Proactive, tech passionate and highly More ❯

Data implementation projects Experience in the definition of Big Data architecture with different tools and environments: Cloud (AWS, Azure and GCP), Cloudera, No-sql databases (Cassandra, Mongo DB), ELK, Kafka, Snowflake, etc. Past experience in Data Engineering and data quality tools (Informatica, Talend, etc.) Previous involvement in working in a Multilanguage and multicultural environment Proactive, tech passionate and highly More ❯

document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud-native platforms (Azure preferred). Collaborate with engineering teams to ensure scalable More ❯

mandatory Experienced building components for enterprise central data platforms (data warehouses, Operational Data Stores, Access layers with APIs, file extracts, user queries) Hands-on experience with SQL, Python, Spark, Kafka Excellent communication skills, including a good working proficiency in verbal and written English About this Job Scopeworker Business Intelligence real time processes enterprise customer data. We develop and maintain More ❯

valuation engines. Strong knowledge of object-oriented programming, data structures, and design patterns. Familiarity with market risk, credit risk, or counterparty risk concepts. Experience with messaging systems (e.g., Solace, Kafka, or RabbitMQ) and distributed architecture. Solid understanding of multi-threaded and low-latency system design. Exposure to quant libraries, risk factor decomposition, or sensitivities is a strong plus. More ❯

Proven problem-solving ability and a track record of meeting deadlines Excellent communication skills for cross-team collaboration Desirable skills (not essential, but a big plus): SSAS, SSRS, SSIS Kafka, MSK, Snowflake, Aurora DB, SNS AWS or Azure database management If you're ready to join a company that challenges limits, delivers excellence, and offers a truly rewarding career More ❯

valuation engines. Strong knowledge of object-oriented programming, data structures, and design patterns. Familiarity with market risk, credit risk, or counterparty risk concepts. Experience with messaging systems (e.g., Solace, Kafka, or RabbitMQ) and distributed architecture. Solid understanding of multi-threaded and low-latency system design. Exposure to quant libraries, risk factor decomposition, or sensitivities is a strong plus. More ❯

valuation engines. Strong knowledge of object-oriented programming, data structures, and design patterns. Familiarity with market risk, credit risk, or counterparty risk concepts. Experience with messaging systems (e.g., Solace, Kafka, or RabbitMQ) and distributed architecture. Solid understanding of multi-threaded and low-latency system design. Exposure to quant libraries, risk factor decomposition, or sensitivities is a strong plus. More ❯

areas Qualifications and Requirements: 5+ years in senior data architecture roles with expertise in distributed systems, high availability, and enterprise leadership experience Proficiency in modern data platforms (Databricks, Snowflake, Kafka), container orchestration (Kubernetes/OpenShift), and multi-cloud deployments across AWS, Azure, GCP Advanced knowledge of Big Data ecosystems (Hadoop/Hive/Spark), data lakehouse architectures, mesh topologies More ❯

areas Qualifications and Requirements: 5+ years in senior data architecture roles with expertise in distributed systems, high availability, and enterprise leadership experience Proficiency in modern data platforms (Databricks, Snowflake, Kafka), container orchestration (Kubernetes/OpenShift), and multi-cloud deployments across AWS, Azure, GCP Advanced knowledge of Big Data ecosystems (Hadoop/Hive/Spark), data lakehouse architectures, mesh topologies More ❯

best practices (Git, Azure DevOps) Enforcing data governance using Azure Purview and Unity Catalog Optimising Spark jobs and SQL queries for performance and cost efficiency Exploring emerging tech like Kafka/Event Hubs and Knowledge Graphs What they're looking for: A strong communicator - someone who can build relationships across technical and business teams Hands-on experience building pipelines More ❯

areas Qualifications and Requirements: 5+ years in senior data architecture roles with expertise in distributed systems, high availability, and enterprise leadership experience Proficiency in modern data platforms (Databricks, Snowflake, Kafka), container orchestration (Kubernetes/OpenShift), and multi-cloud deployments across AWS, Azure, GCP Advanced knowledge of Big Data ecosystems (Hadoop/Hive/Spark), data lakehouse architectures, mesh topologies More ❯