At a Glance
- Tasks: Design and develop high-performance data pipelines for Visa's innovative payment solutions.
- Company: Join Visa, a global leader in payments and technology, making a real impact.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a mission-driven team creating cutting-edge AI models for the future of payments.
- Qualifications: 5+ years in software engineering, strong skills in Apache Spark and Python.
- Other info: Collaborative environment with mentorship opportunities and a focus on continuous improvement.
The predicted salary is between 48000 - 72000 £ per year.
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Company Description
Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.
Job Description
What it's all about - The Payments Foundation Models team is a new, high-impact initiative within Visa's Data Science organization. Based in Cambridge, UK, and working closely with global Visa engineering and product teams, the group's mission is to build the next generation of payments-focused foundation AI models. These models will power a range of premium Risk and Identity Solutions (RaIS) products, such as fraud scores, with the goal of generating more than 100M dollars in new revenue by FY2030, and may be extended into other domains such as credit risk modelling or agentic commerce personalization.
As Senior Consultant Data Engineer you will design, build, optimize, and maintain data tooling and pipelines that power the development and deployment of Visa's Large Transaction Models.
Key Responsibilities
- Design and develop high-performance data pipelines and tooling to support Large Transaction Model training and analysis at global scale.
- Optimize Spark pipelines and workflows for speed and efficiency across Visa's evolving data warehousing and data analytics infrastructure.
- Provide technical leadership and guidance to other members of the agile team, working with cross-functional stakeholders to align technical solutions with product goals.
- Collaborate with data scientists to build production tooling and pipelines for training PyTorch-based machine learning models.
- Ensure data systems meet Visa's standards for security, reliability, scalability, and compliance.
- Mentor junior engineers and contribute to Visa's software engineering best practices.
- Liaise with global technology and product teams to share tools, patterns, and innovations.
- Drive continuous improvement of team processes and shared workflows.
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.
Qualifications
- Academic background to at least undergraduate level in a relevant discipline, e.g., Computer Science, Mathematics, Physics, or Engineering.
- Minimum 5 years experience in collaborative software engineering roles.
- Mastery of Apache Spark in large scale, distributed computing environments.
- Proven track record of optimizing Spark queries for performance at scale.
- Familiarity with typical patterns and trade offs in columnar file formats (e.g., Parquet), open table formats (e.g., iceberg) and analytical query engines.
- Strong experience building and maintaining machine learning pipelines.
- Familiarity with modern software engineering principles and practices (e.g. agile, clean code, IDEs, source control, testing, code review).
- Familiarity with PyTorch models and their integration into production systems.
- Proficiency with data workflow orchestration tools (e.g., Airflow, Luigi, or equivalent).
- Strong programming skills in Python.
- Experience working in Agile or Scrum environments and communicating with non-technical stakeholders.
- Background in payments or financial services data engineering.
- Experience in a technical leadership or management role.
- Familiarity with a systems programming language (e.g., C++ or Rust).
- Experience with Click house.
- Familiarity with inference optimizations for deep learning models.
- Experience with cloud-based big data platforms (e.g., AWS EMR, GCP Dataproc, Azure HDInsight, Databricks).
- Exposure to MLOps practices and tools.
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.
Senior Staff Data Engineer in Cambridge employer: Visa
Contact Detail:
Visa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Staff Data Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those at Visa or similar companies. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Since you're aiming for a Senior Staff Data Engineer role, be ready to discuss your experience with Apache Spark and machine learning pipelines in detail.
✨Tip Number 3
Showcase your leadership skills! Be prepared to share examples of how you've mentored junior engineers or led projects. This will highlight your fit for the technical leadership aspect of the role.
✨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, it shows you're serious about joining the team at Visa.
We think you need these skills to ace Senior Staff Data Engineer in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Staff Data Engineer role. Highlight your experience with Apache Spark, machine learning pipelines, and any relevant projects that showcase your technical leadership skills.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about payments technology and how your background aligns with Visa's mission. Don't forget to mention your experience in Agile environments!
Showcase Your Technical Skills: In your application, be specific about your technical skills. Mention your proficiency in Python, experience with data orchestration tools, and any familiarity with cloud-based platforms. This will help us see how you can contribute to our team.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Visa
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Apache Spark and machine learning pipelines. Be ready to discuss specific projects where you've optimised Spark queries or built production tooling, as this will show your hands-on experience and technical prowess.
✨Showcase Your Leadership Skills
As a Senior Staff Data Engineer, you'll need to provide technical leadership. Prepare examples of how you've mentored junior engineers or led cross-functional teams. This will demonstrate your ability to guide others and align technical solutions with product goals.
✨Understand the Business Impact
Familiarise yourself with Visa's mission and how the Payments Foundation Models team contributes to it. Be ready to discuss how your work can generate revenue and improve risk and identity solutions, showing that you understand the bigger picture.
✨Prepare for Agile Discussions
Since the role involves working in Agile environments, be prepared to talk about your experience with Agile methodologies. Think of examples where you've collaborated with non-technical stakeholders and how you’ve driven continuous improvement in team processes.