1 to 25 of 30 Hadoop Jobs in the UK

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 ❯

ETL processes. Proficiency in Python. Experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data modelling, warehousing, and optimisation. Familiarity with big data frameworks (e.g. Apache Spark, Hadoop). Understanding of data governance, security, and compliance best practices. Strong problem-solving skills and experience working in agile environments. Desirable: Experience with Docker/Kubernetes, streaming data (Kafka More ❯

data modelling, warehousing, and performance optimisation. Proven experience with cloud platforms (AWS, Azure, or GCP) and their data services. Hands-on experience with big data frameworks (e.g. Apache Spark, Hadoop). Strong knowledge of data governance, security, and compliance. Ability to lead technical projects and mentor junior engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience More ❯

experience within either Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands on coding experience, such as Python Reporting tools More ❯

data modelling tools, data warehousing, ETL processes, and data integration techniques. · Experience with at least one cloud data platform (e.g. AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark). · Strong knowledge of data workflow solutions like Azure Data Factory, Apache NiFi, Apache Airflow etc · Good knowledge of stream and batch processing solutions like Apache Flink, Apache More ❯

communication skills We're excited if you have 7+ years of experience delivering multi tier, highly scalable, distributed web applications Experience working with Distributed computing frameworks knowledge: Hive/Hadoop, Apache Spark, Kafka, Airflow Working with programming languages Python , Java, SQL. Working on building ETL (Extraction Transformation and Loading) solution using PySpark Experience in SQL/NoSQL database design More ❯

problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if More ❯

problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if More ❯

AI model development. Expertise in Python, R, or Julia, with proficiency in pandas, NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch. Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.). Strong background in statistical modelling, probability theory, and mathematical optimization. Experience deploying machine learning models to production (MLOps, Docker, Kubernetes, etc.). Familiarity with AWS More ❯

high-quality software features. Strong communication, organisational, and interpersonal skills. Ability to manage multiple priorities in a fast-paced environment. Experience with SQL, NoSQL, and big data platforms (e.g., Hadoop, Spark). Knowledge of cloud security (AWS, Azure, GCP) and data access controls. Proficiency in scripting languages (e.g., Python, Bash) for automation. Certifications such as OSCP, CEH, CISSP, or More ❯

such as Python, R, and SQL for data analysis and model development. Experience working with cloud computing platforms including AWS and Azure, and familiarity with distributed computing frameworks like Hadoop and Spark. Deep understanding of supply chain operations and the ability to apply data science methods to solve real-world business problems effectively. Strong foundational knowledge in mathematics and More ❯

such as Python, R, and SQL for data analysis and model development. Experience working with cloud computing platforms including AWS and Azure, and familiarity with distributed computing frameworks like Hadoop and Spark. Deep understanding of supply chain operations and the ability to apply data science methods to solve real-world business problems effectively. Strong foundational knowledge in mathematics and More ❯

Flows, Conduct>It, Express>It, Metadata Hub, and PDL. Hands-on experience with SQL , Unix/Linux shell scripting , and data warehouse concepts . Familiarity with big data ecosystems (Hadoop, Hive, Spark) and cloud platforms (AWS, Azure, GCP) is a plus. Proven ability to troubleshoot complex ETL jobs and resolve performance issues. Experience working with large-scale datasets and More ❯

Scikit-Learn, Keras, TensorFlow, PyTorch, Mllib) Excellent knowledge of analytical techniques, especially in the field of machine learning and pattern recognition and optimization Experience using Big Data platforms (Spark, Hadoop) for large data volumes You will have knowledge of cloud technology stacks (AWS, GCP, Azure) and data visualization tools and applications (Tableau, Qlickview, PowerBI) You should have very good More ❯

in data modelling, data warehousing, and ETL development. Hands-on experience with Azure Data Factory, Azure Data Lake, and Azure SQL Database. Exposure to big data technologies such as Hadoop, Spark, and Databricks. Experience with Azure Synapse Analytics or Cosmos DB. Familiarity with data governance frameworks (e.g., GDPR, HIPAA). Experience implementing CI/CD pipelines using Azure DevOps More ❯

skills in languages such as Python, R, SQL or Scala, alongside experience of using modern and traditional data technologies including: ElasticSearch, MongoDB, PostgreSQL, mySQL/mariaDB, Oracle, SQL Server, Hadoop, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies. This should be backed with strong cloud-native data More ❯

revenues, liquidity, capital, portfolios) and risk calculations (market risk, credit risk, RWA, Stress Capital Buffer). We operate a scalable analytics stack—distributed compute and GPU clusters, Spark/Hadoop, JupyterHub, ML toolkits, REST APIs, and microservices—to deliver timely, high quality results that inform capital actions and strategic balance sheet management. Also AI is widely used for different More ❯

Banking/Financial Services domain is a plus. Preferred Qualifications Certifications in Pentaho, Big Data, or Cloud Platforms (AWS/GCP/Azure). Experience with Big Data technologies (Hadoop, Spark) and cloud data services. More ❯

e.g. MS SQL, Oracle) NoSQL technologies skills (e.g. MongoDB, InfluxDB, Neo4J) Data exchange and processing skills (e.g. ETL, ESB, API) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies (e.g. Docker) would More ❯

Fabric • Data Visualization: Tableau, Power BI • Additional Tools: Kafka, Snowflake Must-Have Qualifications • SQL Server • PL/SQL • Data Warehousing • Tableau/Power BI Nice-to-Have Qualifications • Snowflake • Hadoop • Experience with cloud databases (AWS RDS, Azure SQL) Requirements Tech Stack & Languages • Tech Stack: SQL, PL/SQL, ETL, • Data Warehousing • Languages: SQL, Python, R Relevant Technologies & Tools • Core More ❯

commercial impact. Understanding of ML Ops vs DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process Video call - high-level overview and initial discussion In-person technical presentation - based on a provided example More ❯

of platform components. Big Data Architecture: Build and maintain big data architectures and data pipelines to efficiently process large volumes of geospatial and sensor data. Leverage technologies such as Hadoop, Apache Spark, and Kafka to ensure scalability, fault tolerance, and speed. Geospatial Data Integration: Develop systems that integrate geospatial data from a variety of sources (e.g., satellite imagery, remote … data-driven applications. Familiarity with geospatial data formats (e.g., GeoJSON, Shapefiles, KML) and tools (e.g., PostGIS, GDAL, GeoServer). Technical Skills: Expertise in big data frameworks and technologies (e.g., Hadoop, Spark, Kafka, Flink) for processing large datasets. Proficiency in programming languages such as Python, Java, or Scala, with a focus on big data frameworks and APIs. Experience with cloud More ❯

e.g. MS SQL, Oracle...) noSQL technologies skills (e.g. MongoDB, InfluxDB, Neo4J...) Data exchange and processing skills (e.g. ETL, ESB, API...) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies (e.g. Docker) would More ❯

Docker and orchestration tools like Kubernetes. Familiarity with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation. Knowledge of data engineering and experience with big data technologies like Hadoop, Spark, or Kafka. Experience with CI/CD pipelines and automation, such as using Jenkins, GitLab, or CircleCI. As an equal opportunities employer, we welcome applications from individuals of More ❯

and social benefits (e.g. UK pension schema) What do you offer? Strong hands-on experience working with modern Big Data technologies such as Apache Spark, Trino, Apache Kafka, Apache Hadoop, Apache HBase, Apache Nifi, Apache Airflow, Opensearch Proficiency in cloud-native technologies such as containerization and Kubernetes Strong knowledge of DevOps tools (Terraform, Ansible, ArgoCD, GitOps, etc.) Proficiency in More ❯