1 to 25 of 55 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 Reporting tools (e.g. Tableau, PowerBI ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Python . Expertise in SQL and large-scale data modelling. Strong cloud experience across GCP, AWS, or Azure . Experience with Databricks, Snowflake, or Hadoop ecosystems . Knowledge of data ingestion, ETL/ELT frameworks, and batch/real-time processing. Applications are now open. #J-18808-Ljbffr ...

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 ...

languages relevant to data engineering (e.g., Python, Scala, Java) and SQL. Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop). Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment. Applicants must possess existing right-to-work ...

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 ...

Life Sciences. Experience working for a software vendor, SaaS provider, or professional services organisation. Familiarity with Ataccama or similar enterprise data platforms. Exposure to Hadoop/Spark, NoSQL, XSLT, Hive, Kafka, Snowflake, or Databricks. Python or other programming languages. Familiarity with SDLC, code management and upgrades, and Unix/ ...

Strong understanding of data structures, algorithms, and software design principles Experience working with large-scale data processing, distributed computing, or cloud-based platforms (e.g., Hadoop, Spark, AWS) is highly desirable Familiarity with ESG investing principles and market trends is a plus Excellent problem-solving, analytical, and debugging skills Strong ...

Python data science ecosystem (e.g. NumPy, Pandas, scikit‐learn, PyTorch, TensorFlow). Experience with big data and distributed analytics platforms (e.g. Spark, Hadoop). Hands‐on experience with Natural Language Processing, graph analytics and advanced analytical methods. Experience using cloud analytics platforms, with strong AWS and native tooling expertise. ...

programming languages relevant to data engineering (e.g., Python, Java, Scala). Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop). Demonstrated ability to lead and mentor junior engineers. Existing right-to-work in the UK is required for this position; foreign applicants should ...

Azure. Advanced analytics, predictive modelling, machine learning, cognitive tools and artificial intelligence. Structured and unstructured data management systems and models, including relational, columnar store, Hadoop and NoSQL platforms. Modern data visualisation platforms such as Tableau, Power BI, Qlik, MicroStrategy and others. IDEALLY WE'D LIKE: Experience in data ...

/DEI, including mappings, workflows, applications, transformations, and reusable components. Support the migration of data assets, ETL pipelines, and workloads from the Cloudera Hadoop platform (HDFS, Hive, Impala, Spark) to AWS Cloud. Design, develop, and optimise data ingestion, transformation, and loading processes into Amazon S3 Data Lake and Amazon ...