1 to 25 of 107 Remote Hadoop Jobs in England

a team-oriented environment. Preferred Skills: Experience with programming languages such as Python or R for data analysis. Knowledge of big data technologies (e.g., Hadoop, Spark) and data warehousing concepts. Familiarity with cloud data platforms (e.g., Azure, AWS, Google Cloud) is a plus. Certification in BI tools, SQL, or More ❯

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 More ❯

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 More ❯

Platform (GCP). Proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or Oracle. Experience with big data technologies such as Hadoop, Spark, or Hive. Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow. Proficiency in at least one More ❯

with programming languages such as Python or Java. Understanding of data warehousing concepts and data modeling techniques. Experience working with big data technologies (e.g., Hadoop, Spark) is an advantage. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Benefits Enhanced leave - 38 days inclusive of 8 UK More ❯

experience in their technologies You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices and design patterns More ❯

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 More ❯

ETL/ELT processes . Experience with data integration tools (e.g., Apache Kafka, Talend, Informatica) and APIs . Familiarity with big data technologies (e.g., Hadoop, Spark) and real-time streaming Expertise in cloud security , data governance , and compliance (e.g., GDPR, HIPAA). Strong SQL skills and proficiency in at More ❯

infrastructure and its impact on data architecture. Data Technology Skills: A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Exposure to ETL/ELT processes, SQL, NoSQL databases is a More ❯

with unstructured datasets. Engineering best practices and standards. Experience with data warehouse software (e.g. Snowflake, Google BigQuery, Amazon Redshift). Experience with data tools: Hadoop, Spark, Kafka, etc. Code versioning (Github integration and automation). Experience with scripting languages such as Python or R. Working knowledge of message queuing More ❯

lakehouse architectures. - Knowledge of DevOps practices, including CI/CD pipelines and version control (eg, Git). - Understanding of big data technologies (eg, Spark, Hadoop) is a plus. 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 ❯

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 ❯

database systems (e.g., PostgreSQL, MySQL) Exposure to cloud platforms such as AWS, Azure, or GCP Experience with big data tools such as Spark and Hadoop Previous experience working with financial data, including understanding of financial metrics and industry trends More ❯

database systems (e.g., PostgreSQL, MySQL) Exposure to cloud platforms such as AWS, Azure, or GCP Experience with big data tools such as Spark and Hadoop Previous experience working with financial data, including understanding of financial metrics and industry trends More ❯

engineering platforms implementation Hands-on development and architecture experience in Java or Scala, Microservices Hands-on development and architecture experience in big-data ecosystem - Hadoop, Hive, Impala, NOSQL Hands-on development, architecture and leadership experience in distributed computing technologies - Spark, Flink Hands-on development, and architecture experience in caching More ❯

The role We are looking for a Data Engineer to join the Data Science & Engineering team in London. Working at WGSN Together, we create tomorrow A career with WGSN is fast-paced, exciting and full of opportunities to grow and More ❯

will be deployed You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Apache Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices & design patterns and More ❯

solve problems with innovative ideas or coding challenges. Familiarity with Agile practices in a collaborative team setting. Exposure to big data tools, such as Hadoop and Spark, for managing large-scale datasets. Experience with cloud platforms like Microsoft Azure. Why Join? They have created a super collaborative culture offering More ❯

data delivery. Building and working with data stores in AWS. Working with stakeholders to analyze and document data requirements. Experience with big data tools (Hadoop, Spark, Kafka, Storm), relational and NoSQL databases, data pipelines (Luigi, Airflow), AWS services, scripting languages (Python, R), and API design. Understanding of FAIR principles. More ❯

and the ability to work in a fast-paced, collaborative environment. Strong communication and interpersonal skills. Preferred Skills: Experience with big data technologies (e.g., Hadoop, Spark). Knowledge of machine learning and AI integration with data architectures. Certification in cloud platforms or data management. More ❯

its data science/ML libraries Agile delivery experience with task estimation and dependency management Excellent communication and collaboration skills Bonus if you have: Hadoop/Jenkins experience Azure or AWS certifications Familiarity with Java Why Join? This employer offers more than just a job - it's a place More ❯

Implementationexperience with Machine Learning models and applications Knowledgeof cloud-based Machine Learning engines (AWS, Azure, Google, etc.) Experiencewith large scale data processing tools (Spark, Hadoop, etc.) Abilityto query and program databases (SQL, No SQL) Experiencewith distributed ML frameworks (TensorFlow, PyTorch, etc.) Familiaritywith collaborative software tools (Git, Jira, etc.) Experiencewith More ❯

Excellent communication skills. Familiarity with Python and its data, numerical, and machine learning libraries. It would be great if you also had: Experience with Hadoop and Jenkins. Azure and AWS certifications. Familiarity with Java. What we do for you: At Leidos, we are passionate about customer success, united as More ❯

automation & configuration management • Ansible (plus Puppet, Saltstack), Terraform, CloudFormation • NodeJS, REACT/MaterialUI (plus Angular), Python, JavaScript • Big data processing and analysis, e.g. Apache Hadoop (CDH), Apache Spark • RedHat Enterprise Linux, CentOS, Debian or Ubuntu. • Java 8, Spring framework (preferably Spring boot), AMQP - RabbitMQ, • Open source technologies • Experience of More ❯