relevant experience in building DW/BI systems · Demonstrated ability in data modeling, ETL development, and Data warehousing. · Strong experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.) · Expertise in a BI solution like Power BI · Hands on experience in modelling databases (particularly nosql), working on indexes more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
AWS SageMaker, or Azure Machine Learning for model development and deployment. Data Analytics and Big Data Technologies: Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
years of Data Architecture Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud Platform). Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka). Experience with marketing analytics tools (e.g., Google Analytics, Adobe Analytics, Salesforce Marketing Cloud) and how to drive key performance indicators. Knowledge of more »
or 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 more »
Deep familiarity with a cloud-native, modern data engineering technology stack. Experience with data ingestion methods and tools. Experience with distributed computing frameworks (e.g., Hadoop, Spark, Hive, Presto). Experience with data orchestration tools. Experience with cloud data warehousing and core data modelling concepts. Proficiency in version control systems more »
Technical Discipline. Technical Expertise: Proficiency in SQL and experience with cloud-based data pipelines (Azure, AWS, GCP). Familiarity with big data tools like Hadoop and Spark. Data Management Skills: Hands-on experience working with large data sets, data pipelines, workflow management tools, and Azure cloud services. Exposure to more »
ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
modern data engineering technology stack compatible with AWS. Experience with web scraping and other data ingestion methods and tools. Knowledge of distributed computing frameworks (Hadoop, Spark, Hive, Presto). Experience with data orchestration tools (Airflow, Orchestra, Azkaban). Expertise in cloud data warehousing and core data modelling concepts. Proficiency more »
ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and deployment. Proficient in big data technologies such as Hadoop, Spark, and Kafka for handling large datasets. Experience with data visualization tools like Tableau, Power BI, or Qlik for deriving actionable insights from data. more »
ETL processes, and data warehousing. - Significant exposure and hands on at least 2 of the programming languages - Python, Java, Scala, GoLang. - Significant experience with Hadoop, Spark and other distributed processing platforms and frameworks. - Experience working with Open table/storage formats like delta lake, apache iceberg or apache hudi. more »
looking for you to demonstrate include: Experience of data storage technologies: Delta Lake, Iceberg, Hudi Sound knowledge and understanding of Apache Spark, Databricks or Hadoop Ability to take business requirements and translate these into tech specifications Knowledge of Architecture best practices and patterns Competence in evaluating and selecting development more »
South East London, England, United Kingdom Hybrid / WFH Options
McGregor Boyall
implement data models, ETL processes, and data warehousing solutions.Programming: Utilize Python, Java, Scala, or GoLang to build and optimize data pipelines.Distributed Processing: Work with Hadoop, Spark, and other platforms for large-scale data processing.Real-Time Data Streaming: Develop and manage pipelines using CDC, Kafka, and Apache Spark.Database Management: Handle more »
London, England, United Kingdom Hybrid / WFH Options
McGregor Boyall
models, ETL processes, and data warehousing solutions. Programming: Utilize Python, Java, Scala, or GoLang to build and optimize data pipelines. Distributed Processing: Work with Hadoop, Spark, and other platforms for large-scale data processing. Real-Time Data Streaming: Develop and manage pipelines using CDC, Kafka, and Apache Spark. Database more »
.Strong knowledge of security principles and best practices for cloud-based solutions.Preferred Skills:Certification in cloud platforms.Experience with big data technologies such as ApacheHadoop, Spark, or Kafka.Knowledge of data governance and compliance frameworks.Familiarity with DevOps practices and tools (e.g., Git, Jenkins, Terraform).HSBC experience is a plusPlease note more »
Sheffield, England, United Kingdom Hybrid / WFH Options
Undisclosed
of security principles and best practices for cloud-based solutions. Preferred Skills: Certification in cloud platforms. Experience with big data technologies such as ApacheHadoop, Spark, or Kafka. Knowledge of data governance and compliance frameworks. Familiarity with DevOps practices and tools (e.g., Git, Jenkins, Terraform). HSBC experience is more »
one leading business intelligence platform (e.g. Microsoft, Crystal, Qlik, SAP, Tableau). Good understanding of open source, big data, and cloud data platforms (e.g. Hadoop, Spark, Hive, Pentaho, AWS, Azure); given a business problem, you can analyse and evaluate options and recommend solutions. Proven experience in designing, building and more »
