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
some Python and AWS data engineering experience, as everything will be related to data ingestion, storage
Role : AWS Data Engineer Location : Johannesburg [ 3 Days in a week from office] Duration : 12 Months are seeking a highly motivated and experienced AWS Data Engineer to join our Global Markets division. In traders, quantitative analysts, and data scientists to design, develop, and maintain data infrastructure and background in C# or Python programming and building data pipelines on AWS, especially with AWS Glue Jobs contributing to the design and implementation of data pipelines to support global markets business. It
We are seeking a skilled and enthusiastic AI Analyst to join our innovative team. The successful candidate to address business challenges.
institution in South Africa, is seeking a Data Solutions Architect to join Purpose
Responsibilities:
Senior Data Engineer Are you a talented senior data engineer looking for your Dream Developer Job? OfferZen 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
partner is looking for a highly analytical Fraud Data Scientist to join their team Job Description: A A leading financial institution is seeking a Data Scientist to join their fight against fraud. In this use your expertise to uncover hidden patterns in data and develop solutions that empower better decision-making Expertise: Provide deep knowledge and guidance for future data-driven projects focused on fraud and analytics. industry-wide and for individual clients. Data Management & Quality: Manage data quality issues related to fraud
partner is looking for a highly analytical Fraud Data Scientist to join their team Job Description: A A leading financial institution is seeking a Data Scientist to join their fight against fraud. In this use your expertise to uncover hidden patterns in data and develop solutions that empower better decision-making Expertise: Provide deep knowledge and guidance for future data-driven projects focused on fraud and analytics. industry-wide and for individual clients. Data Management & Quality: Manage data quality issues related to fraud
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