Intermediate/Senior Data Scientist who can contribute to collecting, analysing, reporting, and interpreting data for development of business strategies. Responsibilities: Use data management systems to deliver prescribed outcomes outcomes. Collect, analyse, report, and interpret data for use in the development of business strategies. Employ mining, modelling, and testing techniques to enable data analysis. Communicate the project status back to 5 years working experience within an analytical, data science or computer science environment SAS SQL
Requirements: Sound knowledge in Python and Java Data Science concepts and principles Experience in tools applications. Architecture and Interface Design. Data modeling and Database technologies (relational,
scouting for a Senior Data Engineer. You will be responsible for developing high quality data warehouse solutions in an Azure environment using Synapse, Data Lake, Azure Data Factory, Wherescape and PowerBI The groups similar fields like Information Systems, Big Data Azure Data Engineer Certification would be advantageous ADF and Data Lake Experience in developing data warehouses and data marts Experience in Data Vault and DataOps environment Experience working with automated data warehousing solutions would be advantageous Minimum
and global reach. We are seeking a talented AWS Data Engineer to become a crucial part of their dynamic to guarantee the accuracy of data transformations. Build resilient data pipelines, leveraging platforms platforms like AWS Glue or Data Pipeline. Craft precise specifications to direct the development, testing, Harness expertise in Oracle SQL, showcasing prowess in data modeling. Create technical documentation and artifacts comprehensively. Employ Data Quality Tools like Great Expectations to maintain data integrity at all levels
management system (DBMS) Set up, maintain reporting and data integration processes using SSRS, SSIS and SSAS relational database structure / architecture Oversee all data generated, monitor server transaction speeds, and
and institutions worldwide is looking for an Azure Data Engineer. The unique position gives a deep insight maintaining Big Data Pipelines using Data Platforms Custodians of data and must ensure that data is shared need-to-know basis Experience using programming skills in data related programming languages and frameworks, such Kusto Experience with Azure Data Solutions: Azure Data Factory, Azure Data Explorer, Azure Databricks Profound technical understanding for Data Engineering and Data Warehouse Design Familiar with modern
every company, globally, by harnessing the value of data using high performance, interoperable and simplified simplified solutions are currently looking for an AWS Data Engineer to join their fast-paced and dynamic team enterprise data solutions and applications Analyse, re-architect and re-platform on-premise data warehouses warehouses to data platforms on AWS cloud using AWS or 3rd party services and Kafka CC. Design and build production production data pipelines from ingestion to consumption within a big data architecture, using Java, PySpark
and IT Methodology processes is recruiting for a Data Scientist – AI Platform to offer a deep insight
focus on health administration has a role for a Data Development Engineer. The purpose of the ETL Developer which will populate the Data Warehouse, develop and enhance the back end of the data warehouse to satisfy Diploma/Degree in Information Technology, Computer Science or data related qualifications 5-10 years' experience in Minimum of 5-10 years Data Warehousing experience. SQL/PLSQL knowledge essential. Data Modelling Tool Experience and implementation of ETL pipelines. Cloud-based data storage solutions like AWS and Azure. Technical
collecting, analysing, reporting, and interpreting data for use in the development of business strategies strategies. Responsibilities Defining and capturing metadata and rules associated with ETL and ELT processes analysis, development and testing of our specialized data and analytical "recipes". Working with clients to to identify and understand their source data systems and data requirements. Perform support activities maintain and enhance data tools and analytical services. Design and develop data models for analytics