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Platform Architect

3 months ago

Midrand, South Africa Liyema Consulting Full time
Key Responsibilities:
- Data Architecture Design:
- Design advanced conceptual, logical, and physical data models, organizations, repositories, dashboards, and reports within a complete functional and technical architecture.
- Advanced Analytics and Machine Learning:
- Develop and implement advanced statistical models and machine learning algorithms to solve business problems.
- Collaboration and Integration:
- Partner with other architects, infrastructure, and software experts to define metadata layers, technical strategies, and optimal integration within the existing client IT landscape.
- Technical Leadership :
- Translate designed solutions to technical designers or developers, review proposed solutions, and optimize them as required.
-Continuous Improvement:
- Design, develop, and continuously improve supporting activities (automation of versioning and release management, scheduling, security models, impact assessment of new changes).
- End-to-End Accountability:
- Be accountable for the end-to-end solution, from conception to deployment.
Project Leadership:
- Lead data projects from conception to deployment.
- Coordinate with cross-functional teams, including product, engineering, and business stakeholders, to ensure successful project delivery.
- Define project scope, goals, and deliverables that support business objectives.
Mentorship and Collaboration:
- Mentor and provide guidance to data specialists.
- Foster a collaborative and innovative team environment.
- Communicate complex technical concepts and insights to non-technical stakeholders.
Research and Development:
- Stay current with the latest advancements in data architecture and the broader data and AI landscape.
- Experiment with new tools, techniques, and technologies to continuously improve data processes and analytics.
Deployment and Maintenance:
- Oversee deployment and monitoring of data solutions in production environments.
- Ensure continuous improvement for existing data pipelines, data models, reports, and infrastructure.
- Implement best practices for data, model management, and version control.
Education:
- Masters or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
Experience:
- 5+ years of experience in data architecture, data engineering, or a related field.
- Proven experience leading data projects and managing teams.
- Extensive experience with big data platforms (cloud and on-premise), data modeling, data analysis, statistical modeling, and machine learning.
Technical Skills:
- Proficiency in programming languages such as Python, R, or Scala.
- Expertise in data processing frameworks like Apache Spark, Hadoop, or similar.
- Proficiency with data modeling tools.
- Strong SQL skills and experience with relational and NoSQL databases.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Advanced knowledge of data visualization tools like Tableau, Power BI, or similar.