Lead Analytics Engineer - Autonomous Networks

About the position

Data Analysis & Engineering Leadership

• Analyse large-scale network, operational, and business datasets to identify trends, dependencies, opportunities, and root causes.
• Develop a deep understanding of data entities, business rules, data lineage, data relationships, and data quality challenges.
• Perform detailed data investigations and validate assumptions through hands-on analysis.
• Lead analytical problem-solving initiatives to improve network efficiency and operational performance.
• Drive data-driven decision-making across network and business domains.

Solution Design & Data Modelling

• Translate business, financial, operational, and network requirements into:
• Data inputs and source requirements
• Data mappings and transformations
• Business rules and allocation methodologies
• Data models and analytical frameworks
• Processing logic and technical specifications
• Define scalable data products and analytics solutions to support network planning and optimization.
• Produce implementation-ready requirements for Data Engineers and development teams.
• Design analytical solutions that support strategic and operational decision-making.

Autonomous Network Enablement

• Contribute to the development of data and orchestration capabilities that enable autonomous networking initiatives.
• Support the evolution of intelligent, data-driven operational processes.
• Work across operational data, orchestration layers, vendor platforms, automation tools, and business logic frameworks.
• Identify opportunities to improve network intelligence, efficiency, performance, reliability, and automation.

Stakeholder Engagement

• Collaborate with Network SMEs, Product Owners, Architects, Finance teams, Business Analysts, Data Engineers, and Engineering teams.
• Facilitate analytical workshops, requirements gathering sessions, and solution design discussions.
• Translate complex technical concepts into meaningful business insights.
• Ensure alignment between business objectives and technical implementation approaches.

Governance & Quality Assurance

• Ensure data products, analytical outputs, and models meet business, operational, and regulatory requirements.
• Drive data governance, quality management, traceability, and accuracy standards.
• Establish analytical design standards and documentation best practices.
• Monitor and improve data quality across multiple data domains.

Minimum Qualifications



Essential



Bachelor's Degree, Diploma, Advanced Diploma, or equivalent qualification in one of the following:

• Data Analytics
• Data Engineering
• Computer Science
• Information Systems
• Telecommunications Engineering
• Network Engineering
• Electronic Engineering
• Mathematics
• Statistics
• Applied Analytics
• Or another relevant quantitative or technology-related field

Preferred

• Postgraduate qualification in Data Analytics, Data Engineering, Telecommunications, Computer Science, Information Systems, or a related field.
• Relevant certifications in:
  • Data Engineering
  • Cloud Platforms
  • Enterprise Data Architecture
  • Telecommunications
  • Network Analytics

Experience Required

• Minimum 8 years' experience within Data Analytics, Data Engineering, Telecommunications, Network Analytics, or similar technical environments.
• Proven experience working with large-scale, complex operational and network datasets.
• Experience designing data products, analytical frameworks, data models, and processing solutions.
• Strong experience translating business requirements into technical specifications and implementation-ready solutions.
• Experience collaborating with business, finance, network operations, and engineering stakeholders.
• Experience within Agile delivery environments.
• Exposure to:
  • Telecommunications Networks
  • OSS/BSS Platforms
  • Network Planning and Optimisation
  • Autonomous Network Programmes
  • Network Performance Management

Technical Skills & Knowledge



Essential

• Advanced analytical and problem-solving skills.
• Strong understanding of:
• Data Modelling
• Data Architecture
• Data Lineage
• Data Governance
• Data Engineering Principles
• Experience with SQL and large-scale data environments.
• Ability to define data transformation rules and analytical logic.
• Strong understanding of operational and business data structures.
• Ability to create implementation-ready specifications for engineering teams.
• Knowledge of automation, orchestration, and autonomous network concepts.

Desired Skills:

• Data Analytics
• Data Engineering
• Telecommunications
• Network Analysis
• SQL