Website:
thecynetgroup.com
Job details:
Job Overview:
Lead the company's enterprise data, analytics, and AI initiatives.
This is a hands-on technical leadership role responsible for defining data and analytics strategy, partnering with business leaders, and building scalable analytics and AI solutions that drive business decisions.
Key Responsibilities
Enterprise Data Leadership:
- Lead the enterprise data strategy, including building a scalable cloud data platform and long-term analytics roadmap.
- Define enterprise data models, KPIs, and governance frameworks to ensure quality, security, and data management best practices.
- Manage role-based access control across all data sources
- Build and manage data ingestion pipelines from structured and unstructured data sources
AI & Analytics:
- Develop AI-powered predictive models and dashboards to drive real-time decision-making and automate reporting.
- Partner with leadership to define KPIs and deliver actionable insights through statistical analysis and machine learning.
Technical Leadership:
- Design and implement modern data architecture, including scalable pipelines that integrate disparate business systems.
- Serve as a technical contributor for SQL, Python, and code reviews, while evaluating and introducing emerging AI tools.
Business Partnership:
- Serve as a trusted advisor to executive leadership, translating complex business challenges into actionable technical solutions.
- Collaborate cross-functionally with business units to influence organisational priorities using data-driven insights.
Team Leadership:
- Build and mentor a high-performing, cross-functional data and analytics team.
- Establish engineering standards and analytics best practices to foster a culture of innovation and continuous improvement.
Qualifications:
- 8+ years in data engineering, analytics, BI, or data science with technical leadership experience.
- Strong Python experience for data engineering and analytics.
- Familiarity with modern AI technologies including LLMs, vector databases, RAG, and AI agents.
- Experience building enterprise data platforms and AI-enabled analytics.
- Tech stack (GCP, BigQuery, Python, AI/LLMs, etc.)
Click on Apply to know more.
