Roles & Responsibilities

You will be involved in architecting, implementing, managing, and running advanced analytics and data platforms. You will assist to establish and implement effective operational workflows, data pipelines, procedures, and best practices in accordance with the university’s infrastructure and security policies to ensure that the platforms are monitored, secure, available, and reliable.

Key Responsibilities

• Lead end-to-end project management for data platform initiatives, ensuring successful delivery according to project goals and objectives.
• Establish and manage the complete machine learning lifecycle.
• Define project scope, objectives, and deliverables in collaboration with stakeholders which align with University’s Outcome.
• Develop and maintain project plans, including timelines, resource allocation, and dependencies.
• Monitor project progress, identify risks, and proactively implement mitigation strategies.
• Coordinate with cross-functional teams to ensure clear communication, collaboration, and alignment throughout the project lifecycle.
• Act as the main point of contact for internal and external stakeholders, providing regular project updates and addressing any concerns or issues.
• Facilitate project meetings, including kick-off meetings, status updates, and post-mortem reviews.
• Drive the implementation of best practices, processes, and tools for efficient project management.
• Collaborate with data stewards, and data analysts to build data pipelines to ingest data from enterprise systems for both batch and real-time streaming data.
• Manage the full life cycle of a data platform project from requirement gathering to data modelling, design of the data architecture and deployment.

Job Requirements

• Degree in Computer Science or Information Technology or related disciplines
• Proven experience (5+ years) in project management with a focus on data platform projects.
• Strong knowledge of project management methodologies and tools, such as Agile or Scrum.
• Strong communication skills (written and verbal) and ability to discuss strategy at the C-level
• Organisational awareness and strong emotional intelligence
• Experience in data architecture, data modelling, data governance, and business knowledge implementing data platforms
• Experience working with a variety of software and services vendors, including SaaS and other cloud-based solutions
• Must have hands-on experience in in implementing Data Lake/Data Warehouse with technologies like – Snowflakes, Databricks, Azure Synapse Analytics, SQL Database, AWS Lake formation.
• Comfortable with DevOps tools like AWS Cloud Formation/Terraform, Docker and Git for CI/CD development.
• Familiar in building REST services is good to have.
• PMP or equivalent and architecture qualifications (i.e. TOGAF) will be added advantage

Tell employers what skills you have

Git
Azure
Pipelines
Scrum
REST
Agile
Information Technology
Data Governance
SQL
Project Management
PMP
Emotional Intelligence
TOGAF
SaaS
Data Architecture
Docker