At a Glance
- Tasks: Lead data engineering strategy and execution for AI-powered products.
- Company: Visa, a global leader in payments technology.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact on data-driven solutions that shape the future of payments.
- Qualifications: 10+ years in data engineering with strong leadership skills.
- Other info: Join a dynamic team focused on innovation and collaboration.
The predicted salary is between 72000 - 108000 £ per year.
Company Description Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world. Progress starts with you.
Job Description What it's all about - Visa is accelerating the delivery of data analytics and AI powered products to support client growth and strategic decision making across regions. We are seeking a Director Head of Data Engineering to lead the design delivery and evolution of scalable data engineering capabilities that underpin Data Science AI and client facing products. This role is accountable for setting the technical direction pace and engineering standards for data platforms pipelines and infrastructure while ensuring strong alignment with Agile product delivery commercial priorities and Global data strategies. The role requires deep hands on data engineering expertise combined with strong leadership and stakeholder management. The Director Head of Data Engineering will guide teams into an AI first era spanning data platforms cloud infrastructure automation and modern engineering practices while ensuring reliable secure and commercially viable delivery.
Primary Responsibilities:
- Own the data engineering strategy and execution across Data Science and Global Data Products ensuring platforms pipelines and tooling are scalable reliable and fit for an AI first future.
- Lead and develop high performing data engineering teams setting clear technical standards engineering best practices and delivery expectations.
- Set the pace and direction for modern data engineering including cloud native architectures data pipelines real time and batch processing platform reliability and automation.
- Guide teams on best practices across data architecture data quality observability security and performance ensuring consistency across regions and teams.
- Partner closely with Product Owners and Agile delivery leads to align data engineering work with product roadmaps sprint planning and delivery prioritisation.
- Ensure delivery priorities are clearly defined sequenced and executed in line with business value client impact and commercial objectives.
- Collaborate closely with senior stakeholders across Data Science Product Consulting Strategy and Commercial teams to align engineering delivery with client and market needs.
- Act as a key interface with Global data engineering and platform teams ensuring regional solutions leverage global capabilities standards and investments.
- Drive the adoption of AI first engineering approaches across infrastructure data platforms and cloud environments enabling faster experimentation and scalable model deployment.
- Ensure strong governance around data security privacy compliance and resilience working in partnership with Risk Legal and Compliance teams.
- Continuously improve engineering efficiency speed to market and cost effectiveness through tooling automation and platform optimisation.
- Support the evaluation and adoption of new technologies platforms and vendors where they create clear technical or commercial advantage.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
Qualifications Basic Qualifications: Bachelor degree in Computer Science Engineering Data or a related technical field or equivalent practical experience. Ten or more years of experience in data engineering platform engineering or related technical leadership roles. Significant experience leading data engineering teams in complex large scale environments. Demonstrated experience working in Agile product delivery models.
Preferred Qualifications: Deep expertise in modern data engineering architectures including cloud platforms data lakes data warehouses streaming technologies and orchestration tools. Strong understanding of AI and machine learning enablement from a data and infrastructure perspective including feature pipelines model deployment and monitoring. Proven ability to set engineering standards and guide teams through technical transformation at scale. Strong commercial mindset with the ability to prioritise engineering work based on business value client impact and return on investment. Experience aligning regional engineering teams with global platforms standards and operating models. Excellent stakeholder management skills with the ability to influence senior technical and non technical leaders. Experience operating in regulated environments with strong awareness of data privacy security and compliance requirements. Comfortable operating in fast changing environments with evolving priorities and dependencies.
Additional Information Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Director - Head of Data Engineering in London employer: Visa
Contact Detail:
Visa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Director - Head of Data Engineering in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Prepare for interviews by researching the company and its culture. Tailor your answers to show how your experience aligns with their goals, especially around data engineering and AI.
✨Tip Number 3
Showcase your skills through projects or case studies. Bring examples of how you've tackled data challenges in the past, especially in large-scale environments.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Director - Head of Data Engineering in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Director - Head of Data Engineering role. Highlight your experience in data engineering, leadership, and Agile methodologies. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our mission at Visa. Keep it engaging and relevant to the job description.
Showcase Your Achievements: Don’t just list your responsibilities; showcase your achievements! Use metrics and examples to demonstrate how you've led teams or improved processes in previous roles. We love seeing tangible results!
Apply Through Our Website: We encourage you to apply through our website for the best chance of success. It’s the easiest way for us to track your application and ensure it gets the attention it deserves. Good luck!
How to prepare for a job interview at Visa
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering knowledge, especially around cloud platforms, data lakes, and streaming technologies. Be ready to discuss how you've led teams in complex environments and the technical standards you've set.
✨Showcase Your Leadership Skills
Prepare examples of how you've developed high-performing teams and guided them through technical transformations. Highlight your experience in Agile product delivery and how you've aligned engineering work with business value.
✨Understand the Business Impact
Be ready to talk about how your engineering decisions have positively impacted clients and the business. Think about specific instances where your work has driven commercial success or improved client satisfaction.
✨Engage with Stakeholders
Demonstrate your stakeholder management skills by discussing how you've collaborated with senior leaders and cross-functional teams. Prepare to explain how you've influenced decisions and aligned engineering efforts with broader company goals.