junior members of the team and influencing them with your vision. Our tech stacks vary between products (such as OracleDB, MongoDB, Elastic Search and Hadoop for data storage and a mixture of commercial-off-the-shelf products and custom applications. We embrace a DevSecOps (Development, Security, and operations) mindset more »
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 »
data preprocessing, feature engineering, and data visualization techniques.Proficiency in working with large-scale datasets, SQL and NoSQL databases, and big data processing frameworks (e.g., Hadoop, Spark).Familiarity with software engineering best practices, including version control, testing, and code review.Strong mathematical and statistical skills, with the ability to apply statistical 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 »
APIs and microservices. Familiarity with data engineering concepts and tools such as data pipelines, ETL processes, SQL, and big data technologies (e.g., Apache Spark, Hadoop). Strong problem-solving skills, analytical thinking, and attention to detail. Excellent communication and collaboration skills, with the ability to work effectively in cross more »
Edinburgh, Scotland, United Kingdom Hybrid / WFH Options
Change Digital – Digital & Tech Recruitment
Glue, AWS Redshift, and Python Experience with ETL processes, data integration, and data warehousing. Strong SQL skills Experience with Big Data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud platforms (AWS, Azure, Google Cloud) Working knowledge of data visualisation tools (PowerBI, Tableau, Qlik Sense) Additional skills: Client more »
Glue, AWS Redshift, and Python Experience with ETL processes, data integration, and data warehousing. Strong SQL skills Experience with Big Data technologies such as Hadoop, Spark, and Kafka Familiarity with cloud platforms (AWS, Azure, Google Cloud) Working knowledge of data visualisation tools (PowerBI, Tableau, Qlik Sense) Additional Skills: Client 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 »
to plan work to maximize the team's productivity and effectiveness. • Deep understanding of the AI development lifecycle • Proficiency in big data technologies like Hadoop, Spark, or similar frameworks. • Excellent skills in data visualization and interpretation. • Demonstrated history of successfully delivering high-quality, data-driven solutions, including deploying production 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 »
large-scale data science/data analytics projects Ability to lead effectively across organizations Hands-on experience with Data Analytics technologies such as AWS, Hadoop, Spark, Spark SQL, Mlib or Storm/Samza Implementing AWS services in a variety of distributed computing, enterprise environments Proficiency with at least one 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 »
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 »
