solutionsData engineering skills: Proficiency in designing, building, developing, and optimizing data pipelines, as well as experience with big data processing tools like Apache Spark, Hadoop, and DataflowExperience in designing & operating Operational Datastore/Data Lake/Data Warehouse platforms at scale with high-availabilityData integration: Familiarity with data integration more »
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 »
/ELT tools.Experience with NoSQL type environments, Data Lakes, Lake-Houses (Cassandra, MongoDB or Neptune).Experience with distributed storage, processing engines such as ApacheHadoop and Apache Spark.Experience with message brokering/stream processing services such as Apache Kafka, Confluent, Azure Stream Analytics.Experience in Test Driven Development (TDD) and 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 »
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 »
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 »
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 »
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 »
computer science, Information Technology, or a related fieldExperience with containerisation and orchestration technologies (e.g., Docker, Kubernetes).Knowledge of big data technologies and frameworks (e.g., Hadoop, Spark).Familiarity with other cloud platforms (e.g. AWS, Google Cloud) and PaaS providers (e.g. Snowflake)Knowledge of Inner or Open Source paradigm and way more »
computer science, Information Technology, or a related fieldExperience with containerisation and orchestration technologies (e.g., Docker, Kubernetes).Knowledge of big data technologies and frameworks (e.g., Hadoop, Spark).Familiarity with other cloud platforms (e.g. AWS, Google Cloud) and PaaS providers (e.g. Snowflake)Knowledge of Inner or Open Source paradigm and way more »
of technology to automate data pipelines and build analytical warehouses· Deep understanding of cloud-based data platforms (Azure SQL DB, Azure Synapse, ADLS, AWS, Hadoop, Spark, Snowflake, No-SQL etc).· Proficient scripting in programming languages such as Java, Python, Scala· Expert in SQLMachine Learning· Good basic understanding of more »
