Vodafone
Data Strategy & Engineering Lead

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About the Role
Digital & IT is a strategic business capability enabling Vodafone to deliver innovative digital products, services, and customer experiences at scale. Achieving this requires an end-to-end, data-led approach across customer journeys, IT systems, and network domains.
The Digital & IT Data Science & Engineering Lead is a critical senior leadership role responsible for establishing data as a strategic product and trusted asset, supporting Vodafone's digital transformation ambitions while ensuring regulatory compliance, operational excellence, and customer confidence. The role is accountable for defining, governing, and delivering end-to-end data, analytics, architecture, and AI capabilities across Digital & IT.
Operating at enterprise scale, the role spans commercial data, digital channels, BSS/IT platforms, and network domains, ensuring data supports product strategy, customer experience, operational performance, and regulatory requirements.
Working in close partnership with Product, Technology, and Business leaders, the role will define the Digital & IT data strategy, establish robust data governance frameworks, and embed data-driven decision-making across products, platforms, and services.
What you'll do
- Define and own the Digital & IT data strategy in partnership with Product leadership, ensuring alignment with product, technology (IT and Networks), and commercial objectives.
- Establish data, analytics, and AI as core enablers of business growth, customer experience excellence, and operational effectiveness.
- Define and maintain a clear, prioritised roadmap covering data platforms, analytics, and AI capabilities.
- Own the end-to-end enterprise data architecture across digital channels, BSS/IT systems, and network domains, in close collaboration with architecture teams.
- Ensure seamless data integration across customer journeys, IT platforms, and network telemetry to enable insight, automation, and predictive capabilities at scale.
- Set and govern enterprise standards for data platforms, pipelines, analytics engineering, and AI solutions.
- Lead the delivery of advanced analytics and AI capabilities from ideation through to production deployment.
- Ensure all data products, models, and insights are production-grade, governed, monitored, and measured for business value.
- Drive high-value data and AI use cases across customer experience, product performance, monetisation, network optimisation, and operational efficiency.
- Ensure data capabilities support the needs of global customers operating across multiple markets and regulatory environments.
- Apply data sovereignty principles, including data residency, access controls, and processing constraints by design.
- Ensure compliance with GDPR and applicable regional data regulations across products, platforms, and services.
- Act as a senior data representative with customers, partners, regulators, and auditors where required.
- Hold end-to-end accountability for the organisation's data governance framework, including policies, standards, controls, and decision forums.
- Embed data governance as a living operational practice across Digital & IT and wider business functions.
- Define and enforce clear data ownership, stewardship, and accountability models.
- Ensure consistent application of data quality, lineage, access control, ethics, and lifecycle management standards.
- Define the operating model for Data Science and Data Engineering, including internal teams, strategic partners, and vendors.
- Influence and align cross-functional teams across Product, Technology, Networks, Operations, and Commercial functions.
- Build and sustain a culture of accountability, innovation, quality, and continuous improvement.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What are we looking for
- Senior leadership experience (5+ years) across Data Architecture, Data Science, Analytics, and Data Engineering within large-scale enterprise environments.
- Deep industry experience (15+ years) spanning Analytics, Digital & IT, Cloud Technologies, and Network/Infrastructure data domains, with a strong understanding of how these areas interconnect.
- Proven delivery of end-to-end data capabilities, covering customer, commercial, IT, and network-related domains from strategy through execution.
- Experience designing and scaling modern cloud-based data platforms, including technologies such as GCP, BigQuery, Dataflow, Dataproc, Azure, AWS, or equivalent solutions.
- Strong understanding of modern data architectures, including data lakes, lakehouse architectures, streaming platforms, real-time processing, and event-driven ecosystems.
- Experience establishing data as a strategic product, enabling business growth, customer value, operational performance, and commercial outcomes.
- Strong track record in defining and embedding enterprise data governance, successfully operating across multiple functions and organisational boundaries.
- Expert knowledge of data sovereignty, GDPR, privacy, and regulatory frameworks, with the ability to translate requirements into practical operating models.
- Experience leading high-performing Data Science, Analytics, and Data Engineering teams, delivering measurable business impact.
- Knowledge of AI, Machine Learning, and Advanced Analytics delivery, including governance, operationalisation, and value measurement.
- Strong stakeholder management and executive communication skills, with the ability to influence senior leaders, customers, and external partners.
- Experience operating within complex global organisations, managing multiple stakeholders, priorities, and regulatory requirements.


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VOIS Equal Opportunity Employer Commitment
Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.
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