1 to 25 of 75 Hadoop Jobs

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 ...

Scala, and SQL. \n Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). \n Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. \n Experience working with cloud‐native data platforms ...

Scala, and SQL. \n Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). \n Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. \n Experience working with cloud‐native data platforms ...

Scala, and SQL. \n Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). \n Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. \n Experience working with cloud‐native data platforms ...

Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop).Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools.Experience working with cloud‐native data platforms, with strong expertise ...

Scala, and SQL. Hands on experience building and operating large scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud native data platforms, with strong expertise ...

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 ...

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 ...

Scala, and SQL.\ NHands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.G. Apache Spark, Hadoop).\ NExperience designingand maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools.\ NExperience working with cloud‐native data platforms, with strong expertise ...

Scala, and SQL.\ NHands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.G. Apache Spark, Hadoop).\ NExperience designingand maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools.\ NExperience working with cloud‐native data platforms, with strong expertise ...

platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data ...

platforms. Strong expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL). Proficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop). Deep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services. Strong programming skills in Python, Java, or Scala for data ...

expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL).\n \n \nProficiency in distributed data processing frameworks (e.g., Spark, Flink, Hadoop).\n \n \nDeep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services.\n \n \nStrong programming skills in Python, Java ...

expertise in SQL, data modelling, and database optimisation (relational, vector and NoSQL).\ N\n\nProficiency in distributed data processing frameworks (e.G., Spark, Flink, Hadoop).\ N\n\nDeep knowledge of cloud data platforms (AWS, Azure, or GCP) and associated services.\ N\n\nStrong programming skills in Python, Java ...

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 ...

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 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, Qlik ...

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 ...

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 ...

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 ...