POSITION OVERVIEW:

The incumbent will be responsible for the strategic planning, development, and implementation of techniques for merging data from various sources into a cohesive, understandable, and useful format. Ensure that data flows seamlessly between systems, maintaining data integrity and supporting the organisations objectives

RESPONSIBILITIES:

Data Integration/Quality and Architecture

Develop and implement data integration solutions to ensure seamless flow of data between disparate systems, databases, and applications.
Responsible for mapping data fields from source systems to target systems, transforming data as necessary to ensure compatibility and maintain data quality.
Design build and manage ETL (Extract, Transform, Load) processes to efficiently transfer data between systems.
Develop workflows, scripts or use ETL tools to automate data movements and transformations.
Implement processing tools to ensure data quality and integrity throughout the integration process, including data cleansing, duplication, and validation.
Continuously monitor and optimised data integration processes to improve efficiency, reliability, and performance, ensuring timely and accurate delivery of data to end-users
Contribute to the development of strategies to improve data integration, analysis and reporting processed within across departments/stakeholders.
Responsible for designing and implementing data architecture that supports efficient integration, transformation, and storage of data across various systems and platforms.
Integrate various software systems, applications, and APIs to facilitate data exchange and interoperability across the organization.

Reporting and Documentation

Provide clear and concise reports to stakeholders, highlighting key findings and recommendations.
Responsible for documenting integration processes, configurations and workflows as well as generating reports to track performance metrics, KPIs and compliance with SLAs.
Participation in organizational AI efforts.

Collaboration and Communication

Collaborate with cross-functional teams to understand business requirements and ensure data integration solutions align with organizational goals.
Communicate and collaborate with data analysts, developers, and business stakeholders to understand data requirements and ensure alignment with business objectives.
Communicate findings and insights in a clear and understandable manner to stakeholders at various levels.
Train end-users on basic functionality

Continuous Improvement

Stay abreast of industry trends and best practices in data integration processes and procedures.
Identify opportunities for process improvements and automation to enhance efficiency.

Risk and Compliance

Ensure that data integration activities comply with data governance policies, privacy laws and security standards.
Evaluate internal processes for efficiency, problems, and inaccuracies.
Responsible for the handling, processing, and cleansing of data.
Identify and resolve issues within the data integration processes and infrastructure.
Monitor system performance, making adjustments as necessary to optimise operations.
Support the implementation of identified key controls and established risk mitigation procedures.
Work closely with IT and other relevant teams to address data quality issues.
Assist with policies and procedures for the collection and analysis of data.

DESIRED SKILLS AND EXPERIENCE

Minimum requirements:

NQF Level 7 in Computer science, Information Technology or related.
6 - 8 Years' experience in the ICT Domain of which at least 4 should be focused on Data.
Knowledge of programming languages like SQL, Python, Java, or R is valuable for manipulating and transforming data, as well as for scripting ETL processes.
A solid understanding of data management principles, including data governance, data quality, data modelling, and data architecture, is essential. This includes knowledge of relational databases, data warehouses, data lakes, and ETL (Extract, Transform, Load) processes.
Experience with data warehousing concepts and technologies is important for designing, implementing, and maintaining data integration solutions. This includes knowledge of dimensional modelling, star and snowflake schemas, and OLAP (Online Analytical Processing) techniques.
Understanding of data security principles and compliance regulations (such as GDPR, HIPAA, or CCPA) is crucial to ensure that data integration processes adhere to legal and regulatory requirements.
Experience with project management methodologies and tools can be beneficial for planning, executing, and monitoring data integration projects, ensuring they are completed on time and within budget.

Preferred

Skills and Competencies

Data Integration Specialist

Key skills