1 to 25 of 121 Hadoop Jobs in London

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 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 ...

Flask, Tornado or Django, DockerExperience working with ETL pipelines is desirable e.g. Luigi, Airflow or ArgoExperience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc.Data acquisition and development of data sets and improving data qualityPreparing data for predictive and prescriptive modellingHands on coding experience, such as PythonReporting ...

driven architectures Airflow dbt Git/GitHub CI/CD Infrastructure as Code Modern data platforms and distributed processing technologies Experience with Databricks or Hadoop-style data processing environments is useful, although candidates with strong transferable experience across modern data platforms will be considered. Customer Data & Retail Context Experience ...

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 ...

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 ...

Azure, GCP).Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop).Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.Understanding of data governance, security, and compliance frameworks.Exposure to AI/ML workloads ...

Azure, GCP) and their AI/ML services.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL, data pipelines, and automated workflows for moving and processing data.Data Governance: Adherence to data governance, security, and privacy standards throughout ...

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 Reporting tools (e.g. Tableau, PowerBI ...

Viya).Relational Databases and Data Warehousing concepts.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.Financial services sector experience.Line management experience.Team building and leading.Mentoring/staff development experience.#TalanUK #LI-HB1QualificationsYou must ...

.• Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).• Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop).• Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.• Understanding of data governance, security, and compliance frameworks.• Exposure ...

similar languages relevant to data manipulation and scripting.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Data Governance: Strong understanding and practical experience with data governance ...

.Hands-on experience building, scaling, and shipping large-scale data platforms in production.Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop).Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis).End-to-end exposure to data pipeline lifecycle development, including extensive ...

traditional patterns remain appropriate – and where modern approaches add measurable value.Data Engineering & Platform Understanding:Strong knowledge of distributed processing (e.g. Apache Spark).Familiarity with Hadoop ecosystem components.Working knowledge of SQL and NoSQL technologies.Understanding of ETL/ELT design trade-offs.Awareness of DevOps practices and CI/CD for data ...

patterns remain appropriate – and where modern approaches add measurable value. Data Engineering & Platform Understanding: Strong knowledge of distributed processing (e.g. Apache Spark).Familiarity with Hadoop ecosystem components. Working knowledge of SQL and NoSQL technologies. Understanding of ETL/ELT design trade-offs. Awareness of DevOps practices and CI/ ...

Python, or similar languages relevant to data manipulation and scripting.Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Familiarity with data modelling techniques (e.g., dimensional, relational) and data ...

deployment.Deep understanding of Quantexa components such as:Entity Resolution (ER)Scoring FrameworkContextual Network GenerationUI ConfigurationStrong background in Big Data technologies, including:Scala, Apache Spark, Hadoop, ElasticSearchExperience with data modelling and design in the context of large-scale analytics platforms.Strong stakeholder management and communication skills – capable of interfacing with both ...

scale ETL development. Proficiency in SQL and programming languages such as Python, Java, or Scala. Hands‐on experience with big data frameworks (e.g., Spark, Hadoop, Flink) and cloud platforms (AWS, GCP, or Azure). Familiarity with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and workflow orchestration tools (e.g., Airflow ...

planningRequired Skills & ExperienceTechnical SkillsStrong proficiency in SQL and data modellingExcellent programming skills in Python, Scala, or JavaHands-on experience with distributed data frameworks (Spark, Hadoop)Experience with data pipelines and ETL toolsExpertise in at least one cloud platform:Azure (Synapse, Data Factory, Databricks)AWS (S3, Glue, Redshift, Lambda ...

Python, SQL, JavaCommercial experience in client-facing projects is a plus, especially within multi-disciplinary teamsDeep 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 ...

deployment and monitoring using CI/CD tools and infrastructure-as-code practices Hands-on expertise with distributed data processing frameworks (e.g., Apache Spark, Hadoop) and real-time data streaming technologies (e.g., Kafka, Kinesis, Spark) Track record of collaborating with cross-functional teams (engineering, analytics, business stakeholders) to deliver ...

query languages such as SQL, PL/SQL, Python, Java, Ruby or R.Experience with relevant modern data technologies such as BigQuery, Databricks, Snowflake, MongoDB, Hadoop, Redis, Kafka or similar.The ability to select technologies based on scalability, performance, security, interoperability and business requirements.Experience documenting complex architectures clearly through diagrams, workflows ...

technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevantYou will also work with internal data management ...

technologies in scope include:Data processing and logic: ANSI SQL, Apache Spark, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevantYou will also work with internal data management ...

comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevant You will also work with ...