6 of 6 Hadoop Jobs in London

Java Commercial experience in client-facing projects is a plus, especially within multi-disciplinary teams Deep knowledge of database technologies: Distributed systems (e.g., Spark, Hadoop, EMR) RDBMS (e.g., SQL Server, Oracle, PostgreSQL, MySQL) NoSQL (e.g., MongoDB, Cassandra, DynamoDB, Neo4j) Solid understanding of software engineering best practices - code reviews, testing ...

Strong proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms like Azure. Knowledge of big data technologies such as Hadoop, Spark, or Kafka. Proficiency in SQL and database management systems. Familiarity with data warehousing concepts and tools. Ability to work collaboratively with cross-functional ...

Strong proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms like Azure. Knowledge of big data technologies such as Hadoop, Spark, or Kafka. Proficiency in SQL and database management systems. Familiarity with data warehousing concepts and tools. Ability to work collaboratively with cross-functional ...

development. Hands-on experience with Azure Data Factory, Azure Data Lake, and Azure SQL Database. Exposure to big data technologies such as Hadoop, Spark, and Databricks. Experience with Azure Synapse Analytics or Cosmos DB. Familiarity with data governance frameworks (e.g., GDPR, HIPAA). Experience implementing CI/CD pipelines ...

plus. Preferred Qualifications Certifications in Pentaho, Big Data, or Cloud Platforms (AWS/GCP/Azure). Experience with Big Data technologies (Hadoop, Spark) and cloud data services. ...

generative AI applications. Perform Exploratory Data Analysis (EDA), data mining, and visualization to extract insights. Design and implement Big Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures. Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods). Implement deep learning architectures (CNN, RNN, LSTM) using … Ensure scalability, security, and compliance of AI systems. Required Skills: Analytical Tools: EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn) Statistical & Multivariate Analysis Big Data: Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark DataLake Architecture, AWS Redshift, Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree ...