1 to 25 of 120 Hadoop Jobs in England

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 ❯

time data pipelines for processing large-scale data. Experience with ETL processes for data ingestion and processing. Proficiency in Python and SQL. Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production More ❯

engineering, architecture, or platform management roles, with 5+ years in leadership positions. Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Spark, Kafka, Hadoop). Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. Proven experience in enterprise-level architecture design and implementation. Hands-on knowledge More ❯

of the following: Python, SQL, 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 frameworks, CI/CD, and More ❯

5+ years of experience working on mission critical data pipelines and ETL systems. 5+ years of hands-on experience with big data technology, systems and tools such as AWS, Hadoop, Hive, and Snowflake Expertise with common Software Engineering languages such as Python, Scala, Java, SQL and a proven ability to learn new programming languages Experience with workflow orchestration tools More ❯

Statistics, Maths or similar Science or Engineering discipline Strong Python and other programming skills (Java and/or Scala desirable) Strong SQL background Some exposure to big data technologies (Hadoop, spark, presto, etc.) NICE TO HAVES OR EXCITED TO LEARN: Some experience designing, building and maintaining SQL databases (and/or NoSQL) Some experience with designing efficient physical data More ❯

cloud environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other similar data modelling approaches. Experience with More ❯

Azure Functions, Azure SQL Database, HDInsight, and Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL: Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI More ❯

Clear communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools to More ❯

Experience of Relational Databases and Data Warehousing concepts. Experience of Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx. Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce. Cross and multi-platform experience. Team building and leading. You must be: Willing to work on client sites, potentially for extended periods. Willing to More ❯

Docker Experience with NLP and/or computer vision Exposure to cloud technologies (eg. AWS and Azure) Exposure to Big data technologies Exposure to Apache products eg. Hive, Spark, Hadoop, NiFi Programming experience in other languages This is not an exhaustive list, and we are keen to hear from you even if you don't tick every box. The More ❯

in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog More ❯

in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based data services (e.g ., AWS Redshift, Azure Synapse Analytics, Goog More ❯

modern data architectures, Lambda type architectures - Proficiency in writing and optimizing SQL - Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS. - Experience with Open Source Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.) - Ability to write code in Python, Ruby, Scala or other platform-related Big data technology - Knowledge of professional software engineering practices & best practices for More ❯

in a similar role. - 3+ years of experience with data modeling, data warehousing, ETL/ELT pipelines and BI tools. - Experience with cloud-based big data technology stacks (e.g., Hadoop, Spark, Redshift, S3, EMR, SageMaker, DynamoDB etc.) - Knowledge of data management and data storage principles. - Expert-level proficiency in writing and optimizing SQL. - Ability to write code in Python More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Data engineering approaches; Database management, e.g. MySQL, Postgress; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector best practice guidance, e.g. ITIL, OGC toolkit. Additional More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector best practice guidance, e.g. ITIL, OGC toolkit. Additional More ❯

build scalable data infrastructure, develop machine learning models, and create robust solutions that enhance public service delivery. Working in classified environments, you'll tackle complex challenges using tools like Hadoop, Spark, and modern visualisation frameworks while implementing automation that drives government efficiency. You'll collaborate with stakeholders to transform legacy systems, implement data governance frameworks, and ensure solutions meet … R; Collaborative, team-based development; Cloud analytics platforms e.g. relevant AWS and Azure platform services; Data tools hands on experience with Palantir ESSENTIAL; Data science approaches and tooling e.g. Hadoop, Spark; Software development methods and techniques e.g. Agile methods such as SCRUM; Software change management, notably familiarity with git; Public sector best practice guidance, e.g. ITIL, OGC toolkit. Additional More ❯

implementing data governance, security standards, and compliance practices. Strong understanding of metadata management, data lineage, and data quality frameworks. Preferred Skills & Knowledge: Familiarity with big data technologies such as Hadoop, Spark, or Kafka Excellent communication skills with the ability to explain complex data strategies to non-technical stakeholders. Outstanding problem-solving abilities and organizational skills. Certifications (Preferred/Desirable More ❯

is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark Streaming) Data manipulation and wrangling techniques Development and deployment technologies (virtualisation, CI tools like Jenkins, configuration management with Ansible More ❯

solving and communication skills, including the ability to convey complex concepts to non-technical stakeholders. Desirable (but not essential): Experience with SSIS, AWS or Azure Data Factory. Familiarity with Hadoop, Jenkins, or DevOps practices including CI/CD. Cloud certifications (Azure or AWS). Knowledge of additional programming languages or ETL tools. This is a fantastic opportunity to take More ❯

e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If More ❯

application Deep understanding in software architecture, object-oriented design principles, and data structures Extensive experience in developing microservices using Java, Python Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark. Good experience in Test driven development and automating test cases using Java/Python Experience in SQL/NoSQL (Oracle, Cassandra) database design Demonstrated ability to be More ❯

and Agile methodologies. - Skilled at handling complex, unstructured datasets. Desirable: - Degree in Data Science, Statistics, or related field. - Experience with cloud platforms (AWS, Azure, GCP), big data tools (Spark, Hadoop), and version control (Git). More ❯