The Risk and Identity Solutions (RaIS) team provides risk management services for banks, merchants, and other payment networks. The Predictive Fraud Intelligence (PFI) team develops core AI/ML products within the Visa Protect suite, empowering clients to detect and prevent fraud throughout the payment lifecycle. The MLOps and Data Engineering team designs and operates the platforms, pipelines, and tooling that enable the core product teams to build, deploy, and iterate on models quickly. This group provides the scalable data foundations, model‑orchestration frameworks, and automated workflows required to keep fraud‑detection models continuously updated against emerging fraud schemes and new attack vectors.

We’re looking for candidates who are passionate about building high‑performance data systems and who thrive on the challenge of working with petabyte‑scale datasets. If you have experience designing efficient, resilient pipelines optimizing distributed data processing and enabling real‑time insights from massive, complex data flows, we want to meet you. This role is an opportunity to apply deep data‑engineering and MLOps expertise to a mission‑critical domain—empowering fraud‑detection models that protect the entire payment lifecycle.

This is a great opportunity to be part of a Data Engineering and MLOps team that is set out to scale and structure large scale data engineering and ML/AI that drives significant revenue for Visa. As a member of the Predictive Fraud Intelligence – MLOps team based out of Bangalore, your role will involve:

• Building and maintaining reliable data pipelines that deliver high‑quality data across the product lifecycle – Product development to client support.
• Developing platforms that support rapid model experimentation, training, evaluation, versioning, and deployment.
• Creating automated monitoring systems for data drift, model performance, and operational health to ensure models stay accurate as fraud patterns evolve.
• Partnering closely with AI/ML researchers and product teams to reduce time from model concept to production.
• Ensuring compliance, security, and traceability across the full ML lifecycle to meet financial‑industry standards.
• Providing self‑service tooling and infrastructure that enables data scientists to iterate quickly while maintaining operational excellence.

We’re looking for a Senior Data Engineer who thrives in an environment of continuous learning and rapid evolution. If you bring a strong growth mindset, embrace complex technical challenges, and enjoy pushing the boundaries of what’s possible with large‑scale data systems, this role is for you

What success looks like:

• You deliver reliable, maintainable data pipelines and services that materially improve how the AI/ML teams train, evaluate, and deploy fraud‑detection models.
• You consistently ship high quality code.
• You demonstrate a strong growth mindset by adopting new technologies, improving existing systems, and contributing fresh ideas to elevate the team’s technical direction.
• You show increasing impact over time—taking on larger, more complex challenges and driving measurable improvements in system reliability, data quality, or developer productivity.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

5+ yrs. work experience with a bachelor’s degree or 4+ years of work experience with a Master's or Advanced Degree in an analytical field such as computer science, statistics, finance, economics, or relevant area. With relevant work experience as a data engineer, analytical engineer as part of a data team.

Technical Skills (Required):

• Strong analytical and problem solving skills.
• Proficiency in Python, Scala, or Java for building production‑grade data systems.
• Solid understanding of data engineering concepts.
• Solid understanding of modern data‑storage technologies (Delta Lake, Iceberg, BigQuery, Snowflake, or equivalent).
• Working knowledge of orchestration and workflow tools such as Airflow, Prefect, Dagster, or Argo.
• Experience working with cloud platforms (AWS, GCP, or Azure) and/or cloud‑native services.
• Strong SQL skills and experience optimizing complex queries for performance.
• Familiarity with data‑quality principles, observability, and monitoring frameworks.
• Ability to debug distributed systems, diagnose performance bottlenecks, and tune pipelines.
• Demonstrated growth mindset—learning new tools, frameworks, and patterns as the data ecosystem evolves.
• Ability to collaborate effectively with data scientists, product managers, and cross‑functional engineering teams.

Preferred skills

• Experience working in fraud detection, risk scoring, payments, or other high‑integrity, compliance‑heavy domains.
• Familiarity with feature‑store design and operations.
• Strong communication skills for partnering with data scientists, product leaders, and engineering leadership.
• Understanding of and interest in Generative AI, large language models, and how they apply to data engineering, MLOps, and developer productivity.
• Experience in end-to-end analytics on any public cloud (preferably AWS)

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.