Job Purpose To ensure that relevant, high-quality data is available in a timely manner for various analytical processes. The data engeering analyst is responsible for understanding the business data and information requirements, the related data flow, business processes and systems that generate the data required as well as the properties, profile and behaviour of the data.  Their outputs includes detailed specifications to produce the data needed, including data flows, detailed dta designs and data models/structures, and source to target mappings with calculations required to enable the provisioning of the data in forms that make it usable for further analytical processing. The Data Analytics Engineer is responsible to streamline the processes, from data collection, data design to provisioning of data that enables decision-making processes and provides insights to business. Job Responsibilities
* Responsible for having a deep understanding of business data and information requirements, the related data flow, business processes and systems that generate the data required as well as the properties, profile and behaviour of the data, provide detailed data specifications for downstream engineering tasks.
* Collaborate with various teams including Data Modelers, Data Engineers,Data Architects, DataGovernance to align data discovery insights and implement basic data solutions.
* Ensure deliverables are delivered according to project plan and budget to meet commitment to stakeholders.
* Perform data testing and validation activities such as error resolution and data quality validation end to end through the data lifecycle.
* Identify and make recommendations to improve or enhance delivery processes.
* Liaise with business stakeholders to elicit and understand data requirements and translate them into technical analytical tasks, aligning efforts with business needs.
* Design, build, and maintain scalable data architecture, including data models, schemas and metadata, to support efficient data storage, retrieval, and analysis.
* Basic understanding of Relational & Dimensional Modelling.
* Basic understanding of data modelling concepts (e.g., normalization, Entities , Attributes , star/snowflake schemas)
* Understanding of data pipelines are built.
* Monitor data pipelines and infrastructure to provide first line support, resolve issues and ensure that the data product meets its SLA timelines for data availability and reliability.
* Create vuirtual views and data extracts for the business in response to business needs.
* Build and maintain API's in collaboration with Data and/or Software Engineers.
* Implement data validation and reconciliation checks in the data pipelines to maintain a high level of data accuracy, consistency and security.
* Monitor and check that data lineage is available.
* Utilisation and adoption of Cloud Technologies and platforms.
* Ensure that all work adheres to regulatory requirements, maintaining compliance with all relevant data policies, privacy standards, and ownership guidelines.
* Deliver accurate, robust, and efficient operational, tactical, and strategic decision‑making insights by leveraging secure, scalable, and optimally designed reporting and analytical platforms that support the business and its client environments.
* Ensures that data access mechanisms are appropriately designed, governed, and tailored to meet the needs of the specific organisational, business, or client context, enabling the right users to access the right insights through the most effective methods.
* Maintain up to date knowledge of latest developments in the Data Engineering Analysis domain, including reading;continuous professional development courses; seminars and conferences.
* Support the achievement of the business strategy, objectives and values.
* Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
* Participate and support corporate responsibility initiatives for the achievement of business strategy. Essential Qualifications - NQF Level
* Advanced Diplomas/National 1st Degrees Minimum Experience Level 5 to Years experience in the following:
* Data Warehousing Principles & Processes Understanding of cloud‑based data storage, compute, and orchestration tools. Data quality management principles
* Strong SQL and Basic API building and maintenance (REST APIs preferred)
* Programming or scripting in Python and or Java
* Data Analytics & Reporting (conceptual understanding) - BI tools Understanding Cloud & Modern Data Stack (e.g., AWS, Azure, GCP)