translate business requirements into Data/IT requirements. Data extraction use multiple languages (Sql) CDEs (Critical Data Elements) source to target mapping (STTM), including knowledge of data dictionaries dictionaries Taxonomies Data Transformation Advanced data analysis using excel (Pivot tables) and the ability to Tools Data Remediation and associated activities: Data Remediation planning and tracking Data quality quality dashboards (design and implementation) Data Governance Compliance Knowledge of project assurance and
management are on a recruitment drive for a Data Scientist to apply data mining techniques and conduct statistical statistical analysis to large, structured and unstructured data sets. Responsibilities: Model complex business problems machine learning models from and utilises distributed data processing and analysis methodologies. Competent such as HDFS / Spark / Kafka. Provide input into Data management and modelling infrastructure requirements systems, are understood and adopted relating to data collection, integration and retention requirements
management services have an open role for a Data Engineer to execute data engineering duties according to the maintain complete data architecture across several application platforms Analyse data elements and systems loading of data Build, create, manage and optimise data pipelines Create data tooling, enabling data consumers consumers in building and optimising data consumption Execute on the design, definition and development of performing root cause analysis on internal and external data and processes Knowledge of integration patterns
searching for a technical specialist. The purpose of the Data Specialist is to use their database, software engineering the necessary data is properly stored on the cloud platform and is available to the data scientists. Experience modelling of data Systems engineering and implementations experience Experience on the data services on Plan Design Data modelling using: Table structures Store Procedures SSIS Packages SQL Cloud Data Services: Implementing data pipelines using cloud infrastructure and services No-SQL experience on the cloud Data engineering
of an Intermediate Data Engineer who will play a crucial role in leveraging data-driven insights to drive measuring the success of data science initiatives. Design and implement data visualisation tools and dashboards with emerging technologies and best practices in data science, machine learning, and artificial intelligence Mathematics, or a related field. 2 years of experience in data analysis, machine learning, and predictive modelling SQL. Experience working with large datasets and data manipulation tools (e.g., Pandas, NumPy) will be
Responsibilities:
Intermediate Data Engineer Are you a talented intermediate data engineer looking for your Dream Developer working as a data engineer Hands-on, practical experience dealing with large amounts of data Experience Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience working in an English speaking environment working with SQL and NoSQL databases Experience with data pipeline and workflow management tools: Azkaban detail Strong analytical skills Ability to combine data from different sources Nice to have: Experience
We are looking for a Data Analyst to join our client in the mining/construction industry based in Elandsfontein Johannesburg. Create data models and reports in a structured data format to enable data ingestion, transformation key business metrics and trends. Identify valuable data sources and automate collection processes, design understandable data visualization techniques. Design and implement data quality and data validation within ensure accuracy and consistency of data. Operate within various departments and assist in continuous business
space and has embarked on an exciting, strategic, data modernization program that will equip them to better looking for someone who can help to ensure that the Data Services deliveries to both internal and external functional, non-functional, and business aspects of the data pipeline and analytics solutions. Identify areas to validate the functionality, performance, and data integrity of the Azure Databricks environment. Utilize reliability of the data pipeline. Data Validation and Quality Assurance: Develop automated data validation scripts
An amazing opportunity for a Senior Data Engineer to join a multinational organization that produces work with feature teams to design and implement data extraction, cleaning, analysis, visualization, and database types to target data containers for the purpose of migrating data to cloud technologies If you Assist in creating data pipelines from source to target platforms. Experience in Data validation and verification to transform data from source to target for analytical purposes (Business Objects/Data Lakes) and migration