1 to 25 of 97 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 ...

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 ...

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/ ...

Science or a related field is preferred. Preferred Skills Familiarity with cloud services like AWS, Google Cloud, or Azure. Experience with big data tools: Hadoop, Spark, Kafka, etc. Knowledge of data integration tools like Informatica, Talend, etc. Understanding of machine learning algorithms and statistics. Experience with data visualization tools ...

. 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 ...

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 ...

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/ ...

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. Team building and leading. Qualifications You must be: Willing to work on client sites ...

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 ...

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 ...

Experience with data warehousing concepts and technologies (e.g., Azure Synapse Analytics, Azure Data Lake Storage). Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) is a plus. Knowledge of data governance and data security best practices. Strong problem-solving skills and attention to detail. Excellent communication ...

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 What We Are Looking ...

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 ...

Server, PostgreSQL, Oracle, MySQL; Data visualisation software: Spotfire, Tableau, or Power BI; Azure cloud computing platform; Big data technologies such as Spark, Elasticsearch, Hadoop; Statistical techniques (regression, clustering etc.); Machine learning and pattern recognition; Front-end web development e.g. HTML, JavaScript; We are looking for tenacious and curious individuals ...

solutions on at least one public cloud platform (AWS, Azure, or GCP)Working knowledge of distributed data systems: Apache Spark, Delta Lake, or equivalent (Hadoop, Kafka, Flink)Experience leading technical customer conversations — discovery, whiteboarding, architecture reviewsFamiliarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data ...

solutions on at least one public cloud platform (AWS, Azure, or GCP)Working knowledge of distributed data systems: Apache Spark, Delta Lake, or equivalent (Hadoop, Kafka, Flink)Experience leading technical customer conversations — discovery, whiteboarding, architecture reviewsFamiliarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data ...

solutions on at least one public cloud platform (AWS, Azure, or GCP) Working knowledge of distributed data systems: Apache SparkTM, Delta Lake, or equivalent (Hadoop, Kafka, Flink) Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming ...

solutions on at least one public cloud platform (AWS, Azure, or GCP) Working knowledge of distributed data systems: Apache SparkTM, Delta Lake, or equivalent (Hadoop, Kafka, Flink) Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming ...

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 ...

such as Pulsar, Kafka, RedPanda. Must have knowledge and experience automatically provisioning and supporting multiple big data technologies; such as MongoDB, DataBricks, Big Query, Hadoop, Spark, Trino, DataLakes/Lakehouse Architectures. Infrastructure management with Terraform Experience with Github or any other source control Knowledge of Scripting/Coding languages ...

/ML offerings. Strong programming skills (Python, Java, C++) and experience with DevOps practices (CI/CD). Knowledge of big data technologies (Hadoop, Spark, Flink). Knowledge of NoSQL databases (MongoDB, Cassandra, DynamoDB), message queueing systems (Kafka, RabbitMQ), and version control systems (Git). Preferred Skills: Hugging Face ...

production. Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles, scalable model deployment, and model governance. Excellent communication and stakeholder management skills with the ability ...

Server, PostgreSQL, Oracle, MySQL; Data visualisation software: Spotfire, Tableau, or Power BI; Azure cloud computing platform; Big data technologies such as Spark, Elasticsearch, Hadoop; Statistical techniques (regression, clustering etc.); Machine learning and pattern recognition; Front-end web development e.g. HTML, JavaScript ...