Reference: NFP014178-RDL-3 Are you a skilled data enthusiast with a knack for business analysis? We are talented individual to join our client's team as a Data Analyst Job Description: Join a leading financial products and processes under analysis Investigate data integrity issues alongside the wider team and propose propose viable solutions Communicate complex data insights to both technical and non-technical stakeholders teams to develop data-driven solutions and strategies Establish and implement data validation protocols
Our client requires the services of a Data Scientist/Engineer (Entry) – Midrand/Menlyn/Rosslyn/Home Office support environments Translating and simplifying requirements DevOps Experience Managing projects / processes Assistant is Important: A clear criminal record is required. NB: By applying for this role, you consent understand and interpret business needs and requirements with an aptitude to move concepts through to give training to fellow colleagues and users when required Willing and able to travel internationally
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 Cooperate with the Business Analyst, Data Architect and Data Visualisation Developer throughout these guidelines and provide valuable input to develop them Requirements: Bachelor's degree in computer science, IT,
Requirements:
healthcare industry is looking for an experienced Data Scientist to join their team. If you come from the these Relevant data science certification such as Python, Microsoft, AWS, Hadoop, Big Data, Machine Learning Infrastructure Requirements: Degree is not negotiable Minimum 5 years experience in data science related notebooks SQL Knowledge and working with large scale data sets Machine learning techniques experience Working Agile environment Experience in operationalizing data science solutions Critical: Experience in a high-scale
refine data collection tools, design, develop, and maintain databases, perform logic-based data validation validation rules for quality assurance on data, timely reporting, and documentation
L performance areas:
Technical Data Management and Analytics
motivated Data Engineer to join their dynamic team as an integration specialist. As a Data Engineer, maintaining their data infrastructure and pipelines. You will collaborate closely with the data scientists, reliable data flows throughout the organisation. The ideal candidate has a strong background in data engineering scalable and efficient data pipelines and ETL processes to ingest, transform, and load data from various sources sources. - Develop and implement data warehousing solutions. - Collaborate with cross-functional teams
of Pretoria / Cape Town is looking for a Senior Data Engineer to join their team on a 12 month contract will be responsible for creating data pipelines to support downstream data delivery. Qualifications: Relevant Diploma / Certification Requirements: Database design skills with an understanding of data warehousing techniques approaches Understanding of and ability to access data from sources such as: Microsoft SQL Server, Oracle maintain data pipelines in support of downstream data delivery Perform analysis on organizational data Create
conceptual understanding of the context and business requirements. Should be able to understand the business needs of advanced data manipulation, complicated programming logic, and large data volumes is required.
Are you passionate about data engineering and ready to make a significant impact? We are seeking a highly highly skilled and motivated Senior Data Engineer If you excel in data architecture, ETL processes, and robust data architectures and ETL processes that support our organisation's data needs and drive data-driven Key Responsibilities: Data Architecture and Modelling: Design and develop data architectures that meet meet the organisation's data requirements. Optimise data models for efficient storage, retrieval, and analysis