1. Data Analysis: Analysing and interpreting complex data using statistical methods and tools to uncover insights and trends. 2. Data Extraction: Using ETL / ELT methods and tools like Azure Data Factory and Synapse Synapse. 3. Data Visualization: Creating visualizations and dashboards to communicate data insights effectively 4. Data Cleaning: Cleaning and preprocessing data to ensure accuracy and completeness. 5. Data Modelling: Working collaboratively with other members of the data science team and other departments to identify business
experience with integration development and support. Experience working with one or more integration platforms like Workato. In-depth understanding of various integration technologies, protocols, and formats: Rest with construction of system architectures that enable well-integrated transactional, collaborative solutions, including RESPONSIBILITIES Plan, develop, test, and deploy integrations and automation between various on-premises and process flows into opportunities for automation/integration while providing feedback towards optimization
PURPOSE OF JOB To design and implement systems integration solutions that support core client systems. KEY AREAS Design technical integration Develop integration systems Perform integration System Testing Conduct Conduct operational management and maintenance of integration systems Maintain key client and stakeholder relations modelling. • Healthcare information systems • Data structures and data transfer mechanisms • Knowledge of HL7 and FHIR messaging protocol an advantage. • Integration Process Design and Specification • Communication
Java Integration Services Developer - 12-Month Contract (Hybrid Work Mode) Location: Sandton, South Africa want you on our team Role Overview: As a Java Integration Services Developer, you'll play a critical role designing, planning, developing, and deploying Java integration services and applications. You'll collaborate tiers of the application, ensuring seamless integration. Apply object-oriented design principles and with Spring Boot, Spring Data, Spring Batch, Spring Webservices, Spring Integration, Spring Rest, and Spring
Prepares, transforms, models data and resolves conflicting sources of data and anomalies • Supports the Agile ceremonies • Implement methods to improve data reliability and quality • Combines raw information formats • Develop and test architectures that enable data extraction and transformation for predictive or entire delivery lifecycle including: system integration testing, performance engineering and unit testing Cooperate with the Business Analyst, Data Architect and Data Visualisation Developer throughout these
processing data from over 200 source systems. The role involves cleaning and aggregating data through our will improve and streamline processes regarding data flow and quality, working both independently and skills
Qualifications
Talend
Prepares, transforms, models data and resolves conflicting sources of data and anomalies Supports the delivery including Agile ceremonies Implement methods to improve data reliability and quality Combines raw information formats Develop and test architectures that enable data extraction and transformation for predictive or entire delivery lifecycle including: system integration testing, performance engineering and unit testing Cooperate with the Business Analyst, Data Architect and Data Visualisation Developer throughout these
The Administrator/Data Capturer is responsible for assisting the Project Manager with administration Project Manager with administration documentation Data Catpturing Collecting invoices Initial ranking of
Join Our Client's Team as a CRM Commercial Data Analyst Our client, a leading global hygiene and health company, is excited to welcome a CRM Commercial Data Analyst to their team in Johannesburg. In this role cross-functional global team Contribute to the development of a data-driven performance mindset/way-of-working across
is in need of a Data Analyst who will be responsible for actively identifying any data conflicts and patterns ensure we have data accuracy, integrity and the best possible datasets for our reports. Data Gathering: Collect Collect data from various sources, ensuring accuracy and completeness. Data Cleaning: Pre-process and and clean data to prepare it for analysis, which might involve handling missing values, outliers, and inconsistencies inconsistencies. Data Analysis: Utilise SQL to query databases and extract relevant information for analysis