talented Data Analyst to join our team at one of the leading Banks in the industry. As a Data Analyst large sets of financial data to support our business operations and drive data-driven decision making Responsibilities: Collect, organize and analyze large sets of data related to the bank's financial operations Develop understand their data needs and provide relevant analysis and insights Develop and maintain data models, dashboards metrics and KPIs Identify patterns and trends in data to inform business strategy and decision making
Technical/Solution Goals
Beneficial
We are seeking a passionate and hands-on Data Engineer to contribute to the development of our revolutionary customers, and stakeholders to establish a robust data pipeline. ● Serve as a cornerstone in the company's with Spark and Airflow. ● Proficient in data pipelines, ETLs, data warehouses, etc. ● Working knowledge demands. We are seeking a passionate and hands-on Data Engineer to contribute to the development of our customers, and stakeholders to establish a robust data pipeline. ● Serve as a cornerstone in the company's
business up for success is searching for a Head of Data Analysis to be a functional leader and get results
innovative financial services have an opportunity for a data engineer who will take responsibility for driving ETL systems for a big data warehouse to implement robust and trustworthy data to support high performing algorithms, predictive models and support real-time data visualisation requirements across the organisation Responsibilities: Systematic solution design of the ETL and data pipeline in line with business user specifications design Ensure data governance and data quality assurance standards are upheld Conduct data design, database
lender by assets, they are looking for a Data Engineer to execute data engineering duties according to the complete data architecture across several application platform Analyse data elements and systems, data flow transformation and loading of data Build, create, manage, and optimise data pipelines, move data pipelines into production enable data consumers to utilise data for reporting purposes Create data tooling, enabling data consumers consumers in building and optimising data consumption, taking integration and usage patterns into account
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
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 quantitative analysts, and data scientists to design, develop, and maintain data infrastructure and pipelines 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
and development of data science and machine learning models; develop cutting-edge data science and machine business value, leveraging internal and external data sources. Skilled in, and continue to improve upon you knowledge of decision science, communicating data, domain modelling, predictive modelling, advanced work closely with cross-functional teams to apply data science and machine learning models to business non-technical audiences. Mentor junior data scientists: mentor junior data scientists, fostering a culture of
We are seeking a meticulous and detail-oriented Data Capturer to join our clients insurance brokerages and efficiently input and update insurance-related data into our databases. The successful candidate will operations within the company. Data Capturing: Enter insurance-related data into the company's database details, claims data, premiums, endorsements, and other relevant insurance-related data. Data Verification: Verification: Review and cross-check the captured data for errors, inconsistencies, or missing information. Make