1 to 25 of 76 Hadoop Jobs in the UK excluding London

Solid understanding of ETL processes , data modeling, and data warehousing. Familiarity with SQL and relational databases. Knowledge of big data technologies , such as Spark, Hadoop, or Kafka, is a plus. Strong problem-solving skills and the ability to work in a collaborative team environment. Excellent verbal and written communication More ❯

AWS Certified Data Engineer, or AWS Certified Data Analytics, or AWS Certified Solutions Architect Experience with big data tools and technologies like Apache Spark, Hadoop, and Kafka Knowledge of CI/CD pipelines and automation tools such as Jenkins or GitLab CI About Adastra For more than 25 years More ❯

data modeling . Experience with relational and NoSQL databases such as Oracle, Sybase, PostgreSQL, SQL Server, MongoDB . Familiarity with big data platforms (e.g., Hadoop, Snowflake). Prior experience with ETL tools or as a SQL developer . Proficiency in Python for data engineering and Tableau for reporting and More ❯

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 More ❯

data architecture, data modelling, ETL/ELT processesand data pipeline development. Competency with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark, Kafka etc). Excellent communication and leadership skills, with the ability to engage and influence stakeholders at all levels. Insightful problem-solving skills More ❯

. Data Platforms: Warehouses: Snowflake, Google BigQuery, or Amazon Redshift. Analytics: Tableau, Power BI, or Looker for client reporting. Big Data: Apache Spark or Hadoop for large-scale processing. AI/ML: TensorFlow or Databricks for predictive analytics. Integration Technologies: API Management: Apigee, AWS API Gateway, or MuleSoft. Middleware More ❯

experience in data engineering, including working with AWS services. Proficiency in AWS services like S3, Glue, Redshift, Lambda, and EMR. Knowledge of Cloudera-based Hadoop is a plus. Strong ETL development skills and experience with data integration tools. Knowledge of data modeling, data warehousing, and data transformation techniques. Familiarity More ❯

Experience in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative More ❯

and deploying machine learning systems into production Experience working with a variety of relational SQL and NoSQL databases Experience working with big data tools: Hadoop, Spark, Kafka, etc. Experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of severless code development Experience with object-oriented More ❯

Engineering: Proficiency in developing and maintaining real-time data pipelines. Experience with ETL processes, Python, and SQL. Familiarity with big data technologies like Apache Hadoop and Apache Spark. MLOps & Deployment: Experience deploying and maintaining ML inference pipelines. Proficiency with Docker and Kubernetes. Familiarity with AWS cloud platform. The Perfect More ❯

Service Catalogue, Cloud Formation, Lake Formation, SNS, SQS, Event Bridge Language & Scripting: Python and Spark ETL: DBT Good to Have: Airflow, Snowflake, Big Data (Hadoop), and Teradata Responsibilities: Serve as the primary point of contact for all AWS related data initiatives and projects. Responsible for leading a team of More ❯

required for this role. Knowledge of cloud-based database solutions (AWS, Azure, Google Cloud) is an advantage. Preferred Qualifications: Experience with big data technologies (Hadoop, Spark, Snowflake) is a plus. Certification in database technologies or testing methodologies. Knowledge of scripting languages like Python or Shell scripting for test automation. More ❯

AWS Databases: MSSQL, PostgreSQL, MySQL, NoSQL Cloud: AWS (preferred), with working knowledge of cloud-based data solutions Nice to Have: Experience with graph databases, Hadoop/Spark, or enterprise data lake environments What You’ll Bring Strong foundation in computer science principles (data structures, algorithms, etc.) Experience building enterprise 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. 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 ❯

recommending scalable, creative solutions. Exposure to some of the following technologies: Python, AWS Redshift, AWS Athena/Apache Presto, Big Data technologies (e.g S3, Hadoop, Hive, Spark, Flink, Kafka etc), NoSQL systems like Cassandra, DBT is nice to have. What you'll get: Full responsibility for projects from day More ❯

contributions to the delivery process, manage tasks, and update teams on progress. Skills & Experience: Proven experience as a Data Engineer with expertise in Databricks, Hadoop/Spark. Strong programming skills in Python, Scala, or SQL, with knowledge of CI/CD platforms. Proficiency with distributed computing frameworks and cloud More ❯

and classification techniques, and algorithms Fluency in a programming language (Python, C,C++, Java, SQL) Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau More ❯

frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). Excellent problem-solving skills and attention to detail. Ability to work independently and as part of a team. Preferred Qualifications: Experience with More ❯

Statistics, Informatics, Information Systems, or another quantitative field. They should also have experience using the following software/tools: Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi More ❯

or Amazon QuickSight. Programming Languages: Familiarity with Python or R for data manipulation and analysis. Big Data Technologies: Experience with big data technologies like Hadoop or Spark. Data Governance: Understanding of data governance and data quality management. A Bit About Us When it comes to appliances and electricals, we 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 ❯

clustering and classification techniques. Fluency in a programming language (Python, C, C++, Java, SQL). Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau). More ❯

. Knowledge of cloud platforms (e.g., Azure). Familiarity with containerization is a plus (e.g., Docker, Kubernetes). Knowledge of big data technologies (e.g., Hadoop, Spark). Knowledge of data lifecycle management. Strong problem-solving skills and attention to detail. Ability to work in an agile development environment. Excellent More ❯

technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications, capabilities, and skills Knowledge of AWS Knowledge of Databricks Understanding of Cloudera Hadoop, Spark, HDFS, HBase, Hive. Understanding of Maven or Gradle About the Team J.P. Morgan is a global leader in financial services, providing strategic advice More ❯