1 to 25 of 30 Hadoop Jobs in London

cloud platforms such as: AWS, Azure, Google Cloud Platform (GCP) Hands-on experience with data technologies such as: Apache Spark, Databricks, Kafka, Airflow, Snowflake, Hadoop ecosystems Experience designing and maintaining data warehouses and data lakes. Knowledge of DevOps and CI/CD tooling (e.g. Git, Jenkins, Azure DevOps, Terraform ...

Docker \n Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo \n Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. \n Data acquisition and development of data sets and improving data quality \n Preparing data for predictive and prescriptive modelling \n Hands ...

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 ...

Django, Docker\ NExperience working with ETL pipelines is desirable e.G. Luigi, Airflow or Argo\ NExperience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc.\ NData acquisition anddevelopment of data sets and improving data quality\ NPreparing data for predictive and prescriptive modelling\ NHands on coding experience, such ...

Docker \n Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo \n Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. \n Data acquisition and development of data sets and improving data quality \n Preparing data for predictive and prescriptive modelling \n Reporting ...

Django, Docker \ NExperience working with ETL pipelines is desirable e.G. Luigi, Airflow or Argo \ NExperience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc.\ NData acquisition anddevelopment of data sets and improving data quality \ NPreparing data for predictive and prescriptive modelling \ NReporting tools (e.G. Tableau, PowerBI, Qlik ...

quality checks into pipelines. Knowledge of cloud infrastructure (AWS, Azure, or GCP) and database technologies including relational and non-relational stores such as Postgres, Hadoop, Elasticsearch, and Graph databases. Solid understanding of coding best practices, design patterns, CI/CD tooling, versioning, dependency management, error handling, monitoring, and alerting. ...

data mesh Strong understanding of best practice DataOps and MLOps Up-to-date understanding of various data engineering technologies including Apache Spark, Databricks and Hadoop Strong understanding of agile ways of working Up-to-date understanding of various programming languages including Python, Scala, R and SQL Up-to-date ...

data mesh\ NStrong understandingof best practice DataOps and MLOps\ NUp-to-date understanding of various data engineering technologies including Apache Spark, Databricks and Hadoop\ NStrong understandingof agile ways of working\ NUp-to-date understanding of various programming languages including Python, Scala, R and SQL\ NUp-to-date understanding ...

skills in Python, with a command of data science libraries (e.g., Pandas, NumPy, Scikit‐learn). Experience with big data technologies (e.g., Spark, Trino, Hadoop) and ideally cloud platforms (e.g., AWS, GCP, Azure) for scalable data processing, storage, and model deployment. Ideally having understanding and practical experience with graph ...

skills in Python, with a command of data science libraries (e.g., Pandas, NumPy, Scikit‐learn). Experience with big data technologies (e.g., Spark, Trino, Hadoop) and ideally cloud platforms (e.g., AWS, GCP, Azure) for scalable data processing, storage, and model deployment. Ideally having understanding and practical experience with graph ...

infrastructure underpinning data systems through a DevOps approach Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop Good understanding of the possible architectures involved in modern data system design (e.g. Data Warehouse, Data Lakes and Data Meshes) and the different ...

infrastructure underpinning data systems through a DevOps approach\ NKnowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop\ NGood understanding of the possible architectures involved in modern data system design (e.G. Data Warehouse, Data Lakes and Data Meshes) and the different ...

unstructured datasets. Strong stakeholder management and communication skills. Desirable Insurance or financial services experience, ideally within pricing, underwriting, fraud, or claims. Experience with Spark, Hadoop, NoSQL, or modern big data platforms. Agile delivery experience and collaborative software development practices. Experience leading analytics teams and driving organisational change. Robert Walters ...

based ensembles (and experience applying them with packages like Pandas, sci-kit-learn, SciPy) is highly beneficial\ NExperience processing big data, ideally in a Hadoop/Spark environment, would be beneficial\ NProven experience implementing CI/CD and DevOps practices, with the ability to improve deployment reliability, testing standards ...

based ensembles (and experience applying them with packages like Pandas, sci-kit-learn, SciPy) is highly beneficial Experience processing big data, ideally in a Hadoop/Spark environment, would be beneficial Proven experience implementing CI/CD and DevOps practices, with the ability to improve deployment reliability, testing standards ...

emerging data technologies, products and delivery approaches Familiarity with cloud platforms such as Azure, AWS or GCP, alongside technologies including Databricks, Snowflake, Power BI, Hadoop, SQL and Python Experience working with delivery methodologies including Agile, SAFe and Waterfall Strong proficiency with tools such as Jira, Confluence and Planview ...

Relational databases (SQL Server, PostgreSQL, Oracle, MySQL) Data visualisation tools (Power BI, Tableau, Spotfire) Cloud platforms, particularly Microsoft Azure Big data technologies (Spark, Elasticsearch, Hadoop) Statistical modelling and advanced analytics Machine learning and pattern recognition techniques Web technologies such as HTML and JavaScript ...

proficiency in machine learning frameworks and programming languages such as Python, R, or similar. Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL). Familiarity with anomaly detection, supervised, unsupervised learning methods, deep learning, and graph based solutions Demonstrated ability to work collaboratively in cross ...

machine learning frameworks and programming languages such as Python, R, or similar.\ N\n\nExperience working with large datasets and data processing technologies (e.G., Hadoop, Spark, SQL).\ N\n\nFamiliarity with anomaly detection, supervised, unsupervised learning methods, deep learning, and graph based solutions\ N\n\nDemonstrated ability ...

About the Job you are considering: Results-driven Hadoop Data Engineer with experience designing, developing, and maintaining large-scale data processing solutions for financial services organizations. Skilled in building robust data pipelines, managing big data platforms, and transforming high-volume structured and unstructured financial data into actionable insights. Proficient … Hadoop ecosystem technologies including HDFS, Hive, Spark, Sqoop, Kafka, Oozie, and YARN , along with SQL and cloud-based data platforms Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend ...

Docker, Kubernetes) Nice to have: Experience with CI/CD pipelines (GitLab, Jenkins) Exposure to data tooling (Airflow, NiFi, Elasticsearch) Experience with Cloudera/Hadoop ecosystems (Spark, Hive, HDFS) Why join? Work on modern data platforms at scale Collaborate with data scientists and engineering teams Opportunity to shape platform ...

Strong technical skills in Python and SQL, including building data pipelines and working with large-scale datasets and distributed data platforms (e.g., BigQuery, Snowflake, Hadoop or similar) Experience applying data science, machine learning, or data engineering approaches within data-intensive domains such as Finance or Operations Proficiency with ...

Preferred qualifications, capabilities, and skills Experience designing/implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray). Experience with big data technologies (e.g., Spark, Hadoop). Have constructed batch and streaming microservices exposed as REST/gRPC endpoints. Familiarity with GraphQL. We recognize that our people are our strength ...

Experience with modeling tools such as R, scikit‐learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting ...