1 to 25 of 46 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 Reporting tools (e.g. Tableau, PowerBI ...

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 ...

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 ...

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 ...

phases of the system development life cycle Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Data bricks, MySQL, Oracle, PostgresSQL, Hadoop, Snowflake, etc.) Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of modern data warehouse capabilities and technologies such ...

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 ...

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 ...

decisions and the trade-offs behind them. Demonstrable experience leading data estate modernisation, such as moving from legacy data warehouses, on-premises databases or Hadoop to modern cloud or hybrid data platforms. Deep expertise in at least one modern data platform (Databricks, Snowflake or Microsoft Fabric), plus a working ...

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 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 ...

experience (focus on machine learning): SQL and Python’s Data Science stack; good knowledge of at least one big data framework (e.g., PySpark, Hive, Hadoop) is a plus. R, SPSS, and SAS are considered nice-to-have Strong understanding of machine learning methods and experience applying them to complex ...

identifying and managing sales opportunities at client engagements An understanding of database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. Hadoop, Mahout, Pig, Hive, etc. An understanding of statistical modelling techniques e.g. Classification and regression techniques, Neural Networks, Markov chains, etc. An understanding of cloud ...

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 ...

Ability to read through code, especially Java. Demonstrable experience collaborating with engineering on services Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL) Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis Experience with statistical analysis and good presentation skills ...

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 ...

about you: Strong Python knowledge. Ability to read through code. Demonstrable experience collaborating with engineers. Experience with big data technologies such as Hadoop, Spark, or similar. Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions. Strong knowledge in at least a few of the following areas ...

Strong understanding of Apache HTTP, Envoy, and REST API design. Experience working with Protobuf, Avro, and Parquet data formats. Knowledge of Iceberg, Databricks, and Hadoop ecosystems. Skills that will help Follows TDD, ATDD and Clean Coding practices and used to setting up or working in an environment using ...

platform engineering standards using Databricks Asset Bundles (DABs), Terraform and Azure DevOps or GitHub Actions Lead migrations from legacy platforms (SQL Server, Oracle, SAS, Hadoop, Synapse) with clear cut-over and reconciliation plans Monitor and optimise DBU consumption and cluster policies, giving the client clear cost visibility Enable MLOps ...

from kernel, networking, storage, to applications Work in Python to design and deliver open source code Architect cloud infrastructure solutions like OpenStack, Kubernetes, Ceph, Hadoop and Spark either On-Premises or in Public Cloud (AWS, Azure, Google Cloud) Coach and develop your colleagues where you have insights Grow ...