Data Integration & AI Architect at AECI Limited

Job Description

• The Data Integration & AI Architect plays a crucial role in designing and managing data ecosystems (platforms) that support AI-driven decision-making.

Key Performance Areas:

• Data Flow Optimization – Ensuring seamless data movement across platforms to enhance accessibility.
• Reducing Data Silos – Integrating disparate data sources to create a unified and consistent data environment.
• AI Infrastructure Design – Building scalable architectures that support AI models and machine learning applications.
• Data Governance & Security – Implementing policies to ensure data integrity, compliance, and protection.
• Decision-Making Enhancement – Leveraging integrated data insights to improve business intelligence and strategic planning

Key Performance Indicators:

• Measuring the speed and reliability of data extraction, transformation, and loading
• Ensuring high availability of integrated data platforms.
• Evaluating the effectiveness of AI predictions
• Assessing improvements in automation and workflow optimization
• Tracking the accuracy of AI-driven forecasts.

Qualifications & Experience

• Bachelor’s Degree – A degree in Computer Science, Data Science, Information Technology, or Software Engineering

Advantageous:

AI & Machine Learning Certifications:

• AWS Certified Machine Learning – Specialty – Focuses on AI and ML solutions in AWS.
• Microsoft Certified: Azure AI Engineer Associate – Covers AI solutions in Azure.
• Google Professional Machine Learning Engineer – Specializes in AI and ML on Google Cloud.

Data Integration & Cloud Certifications:

• Certified Data Management Professional (CDMP) – Covers data governance and integration.
• Google Cloud Certified – Professional Data Engineer – Focuses on data processing and integration.
• IBM Certified Data Architect – Big Data – Specializes in big data architecture
• A Data Integration & AI Architect requires minimum 10 years’ experience in data management, cloud computing, and AI-driven solutions

Technical Skills:

• Data Integration – Expertise in ETL processes, APIs, and data pipelines.
• AI & Machine Learning – Strong understanding of deep learning, NLP, and predictive analytics.
• Cloud Platforms – Experience with AWS, Azure, or Google Cloud.
• Big Data Technologies – Proficiency in Hadoop, Spark, NoSQL databases, and data lakes.
• Security & Compliance – Knowledge of data protection, encryption, and regulatory standards.

Knowledge (professional experience)

• Solution Architecture – Designing scalable AI and data integration solutions.
• Stakeholder Collaboration – Working with business leaders to align AI strategies with company goals.
• Data Governance – Implementing policies for data integrity, compliance, and security.
• Performance Optimization – Enhancing AI models and data pipelines for efficiency

Behaviours (Attributes)

• Problem-Solving – Ability to troubleshoot complex data and AI challenges.
• Communication – Clear articulation of technical solutions to stakeholders.
• Leadership – Guiding teams in AI adoption and data integration strategies.
• Strategic Thinking – Aligning AI and data solutions with business objectives.

Closing Date

• 2025/07/25