4 of 4 Hadoop Jobs in Leicestershire

professional experience Preferred Skills: Experience working within the public sector. Knowledge of cloud platforms (e.g., IBM Cloud, AWS, Azure). Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop). Understanding of data warehousing concepts and experience with tools like IBM Cognos or Tableau. Certifications:While not required, the following certifications would be highly beneficial: Experience working within … the public sector. Knowledge of cloud platforms (e.g., IBM Cloud, AWS, Azure). Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop). Understanding of data warehousing concepts and experience with tools like IBM Cognos or Tableau. ABOUT BUSINESS UNIT IBM Consulting is IBM's consulting and global professional services business, with market leading capabilities in business and More ❯

Scala. Experience with SQL, NoSQL, visualization tools, and statistical packages. Analytical and problem-solving skills. Experience with social media analytics and user behavior. Knowledge of big data technologies like Hadoop, Spark, Kafka. Understanding of AWS machine learning services like SageMaker and Comprehend. Experience with data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and More ❯

security clearance. We do not sponsor visas. Preferred Skills and Experience Public sector experience Knowledge of cloud platforms (IBM Cloud, AWS, Azure) Experience with big data frameworks (Apache Spark, Hadoop) Data warehousing and BI tools (IBM Cognos, Tableau) Additional Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology Industries: IT Services and Consulting #J More ❯

e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP More ❯