201 to 225 of 541 Hadoop Jobs in England

incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical More ❯

incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical More ❯

incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical More ❯

incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases). − Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage − Familiarity with data warehousing solutions and cloud data platforms. − Background in building applications wrapped around AI/LLM/mathematical More ❯

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 More ❯

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 More ❯

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 More ❯

experience with container systems (Docker, Kubernetes) Proven experience with AWS services (Lambda, S3, EMR, DynamoDB) Hands-on experience with big data technologies such as Hadoop, Spark, Snowflake, and Vertica Familiarity with CI/CD, DevOps practices, and automated testing frameworks Ability to work in agile, fast-paced environments and More ❯

including SQL and NoSQL databases, and data services ecosystems (ADF, SQL DWH, Data Bricks). Experience in Distributed Data Computing and Big Data ecosystems (Hadoop, Cassandra, Teradata). Experience with designing and building APIs. Other/Beneficial skills Previous experience in Finance/payments/insurance industries. Experience with More ❯

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 More ❯

Java, C++) and experience with DevOps practices (CI/CD). Familiarity with containerization (Docker, Kubernetes), RESTful APIs, microservices architecture, and big data technologies (Hadoop, Spark, Flink). Knowledge of NoSQL databases (MongoDB, Cassandra, DynamoDB), message queueing systems (Kafka, RabbitMQ), and version control systems (Git). Preferred Skills: Experience More ❯

TensorRT and Experience with NVIDIA GPU hardware and software stack. Understanding of HPC and AI workloads. Familiarity with BigData platforms and technologies, such as Hadoop or Spark. What We Offer: • Opportunity to work with a leading company • An opportunity to be part of impactful projects that shape the future More ❯

based data systems Clear communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: 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 More ❯

would be great if you also had: Experience of configuring and using ETL platforms such as SSIS, AWS or Azure Data Factory Experience of Hadoop and Jenkins Azure Certified AWS Certified Familiarity with Java Knowledge of DevOps practices, including CI/CD pipelines What we do for you: At More ❯

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 More ❯

Java is a big plus. Experience using ELK Stack (Elasticsearch, Logstash, Kibana). Experience using business intelligence tools (e.g., Tableau) and data frameworks (e.g., Hadoop). Experience with AI/ML-based solutions for data analysis is a big plus. Analytical mind and business acumen. Strong math skills (e.g. More ❯

or related industries. Certification in relevant areas (e.g., AWS Certified Data Analytics, Google Data Analytics Professional Certificate). Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure). Experience with data visualization design principles and storytelling techniques. Knowledge of agile methodologies and project management. More ❯

with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams with diverse More ❯

Science, Engineering, Mathematics, Physics or a related field. Hands-on experience with LLMs, RAG, LangChain, or LlamaIndex. Experience with big data technologies such as Hadoop, Spark, or Kafka. The estimated total compensation range for this position is $75,000 - $90,000 ( USD base plus bonus). Actual compensation for More ❯

Science, Engineering, Mathematics, Physics or a related field. Hands-on experience with LLMs, RAG, LangChain, or LlamaIndex. Experience with big data technologies such as Hadoop, Spark, or Kafka. The estimated total compensation range for this position is $75,000 - $90,000 ( USD base plus bonus). Actual compensation for More ❯

of stakeholders and cross-functional teams, performing analysis of their data requirements and documenting it. Big data tools and stream-processing systems such as: Hadoop, Spark, Kafka, Storm, Spark-Streaming. Relational SQL and NoSQL databases, including Postgres and Cassandra. Experience designing and implementing knowledge graphs for data integration and More ❯

of stakeholders and cross-functional teams, performing analysis of their data requirements and documenting it. Big data tools and stream-processing systems such as: Hadoop, Spark, Kafka, Storm, Spark-Streaming. Relational SQL and NoSQL databases, including Postgres and Cassandra. Experience designing and implementing knowledge graphs for data integration and More ❯

on data accuracy, quality, and reliability Desirable (Nice to Have): Background in defence, government, or highly regulated sectors Familiarity with Apache Kafka, Spark, or Hadoop Experience with Docker and Kubernetes Use of monitoring/alerting tools such as Prometheus, Grafana, or ELK Understanding of machine learning algorithms and data More ❯

on data accuracy, quality, and reliability Desirable (Nice to Have): Background in defence, government, or highly regulated sectors Familiarity with Apache Kafka, Spark, or Hadoop Experience with Docker and Kubernetes Use of monitoring/alerting tools such as Prometheus, Grafana, or ELK Understanding of machine learning algorithms and data More ❯

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 More ❯