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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
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.