1 to 25 of 167 Hadoop Jobs in the UK

technical concepts to non-technical stakeholders. Team Player: Ability to work effectively in a collaborative team environment, as well as independently. Preferred Qualifications: Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka). Familiarity with AWS and its data services (e.g. S3, Athena, AWS Glue). Familiarity with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake). Knowledge of containerization More ❯

Azure, or Google Cloud Platform (GCP). Strong 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 Python and at least one other programming language 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 ❯

pipelines and ETL - informatica - Experience in SQL and database management systems - Knowledge of data modelling , warehousing concepts , and ETL processes - Experience with big data technologies and frameworks such as Hadoop, Hive, Spark. Programming experience in Python or Scala. - Demonstrated analytical and problem-solving skills. - Familiarity with cloud platforms (e.g Azure , AWS ) and their data related services - Proactive and detail 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 ❯

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 ❯

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 ❯

tools and libraries (e.g. Power BI) Background in database administration or performance tuning Familiarity with data orchestration tools, such as Apache Airflow Previous exposure to big data technologies (e.g. Hadoop, Spark) for large data processing Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions. Strong communication 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 ❯

Familiarity with Data Mesh, Data Fabric, and product-led data strategies. Expertise in cloud platforms (AWS, Azure, GCP, Snowflake). Technical Skills Proficiency in big data tools (Apache Spark, Hadoop). Programming knowledge (Python, R, Java) is a plus. Understanding of ETL/ELT, SQL, NoSQL, and data visualisation tools. Awareness of ML/AI integration into data architectures. More ❯

needs, entrepreneurial spirit Excellent verbal and written communication skills BS or MS degree in Computer Science or equivalent Nice to Have Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark Experience in developing Finance or HR related applications Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda Working experience More ❯

needs, entrepreneurial spirit Excellent verbal and written communication skills BS or MS degree in Computer Science or equivalent Nice to Have Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark Experience in developing Finance or HR related applications Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda Working experience More ❯

needs, entrepreneurial spirit Excellent verbal and written communication skills BS or MS degree in Computer Science or equivalent Nice to Have Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark Experience in developing Finance or HR related applications Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda Working experience More ❯

needs, entrepreneurial spirit Excellent verbal and written communication skills BS or MS degree in Computer Science or equivalent Nice to Have Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark Experience in developing Finance or HR related applications Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda Working experience 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 ❯

projects Skills & Experience: Proven experience as a Lead Data Solution Architect in consulting environments Expertise in cloud platforms (AWS, Azure, GCP, Snowflake) Strong knowledge of big data technologies (Spark, Hadoop), ETL/ELT, and data modelling Familiarity with Python, R, Java, SQL, NoSQL, and data visualisation tools Understanding of machine learning and AI integration in data architecture Experience with More ❯

and with customers Preferred Experience Degree in Computer Science or equivalent practical experience Commercial experience with Spark, Scala, and Java (Python is a plus) Strong background in distributed systems (Hadoop, Spark, AWS) Skilled in SQL/NoSQL (PostgreSQL, Cassandra) and messaging tech (Kafka, RabbitMQ) Experience with orchestration tools (Chef, Puppet, Ansible) and ETL workflows (Airflow, Luigi) Familiarity with cloud More ❯

and with customers Preferred Experience Degree in Computer Science or equivalent practical experience Commercial experience with Spark, Scala, and Java (Python is a plus) Strong background in distributed systems (Hadoop, Spark, AWS) Skilled in SQL/NoSQL (PostgreSQL, Cassandra) and messaging tech (Kafka, RabbitMQ) Experience with orchestration tools (Chef, Puppet, Ansible) and ETL workflows (Airflow, Luigi) Familiarity with cloud 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 ❯

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 ❯

flow diagrams, and process documentation. MINIMUM QUALIFICATIONS/SKILLS Proficiency in Python and SQL. Experience with cloud platforms like AWS, GCP, or Azure, and big data technologies such as Hadoop or Spark. Experience working with relational and NoSQL databases. Strong knowledge of data structures, data modeling, and database schema design. Experience supporting data science workloads with structured and unstructured 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 ❯

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 ❯

one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience mentoring team members on best practices PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience operating large data warehouses Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make More ❯