About the job
At Visa, we are committed to making our payment technology accessible to everyone, everywhere. The success of our key bank and merchant partners, along with our internal business units, is vital in achieving this goal. Within the Global Data Solutions organization, we harness an extensive data set that includes over 3 billion cards globally to support our partners. The Visa Consulting & Analytics (VCA) Data Science team plays a pivotal role in this organization, composed of high-performing data scientists, analysts, and engineers dedicated to helping major organizations navigate the evolving landscape of technology, finance, and commerce through innovative and advanced analytic solutions. Our mission is to develop creative solutions that make an immediate impact on our highly analytical partners' businesses.
As we continue to expand, we are seeking a passionate Machine Learning Engineer to join our vibrant team in Bengaluru. The ideal candidate will possess deep expertise in big data and ML engineering, enabling the creation of large-scale data processing systems utilizing the latest database and data processing technologies. This pan-regional role is essential in empowering data platforms that Data Scientists, Analysts, and BI Users leverage to deliver impactful solutions for Visa clients.
Principal Responsibilities:
- Design and maintain optimal data pipelines, data marts, and architectures based on our Global Technology Stack.
- Collaborate with the global data engineering team to implement global engineering standards in the Asia Pacific region.
- Support operations, DevOps, and MLOps processes for data engineering and data science jobs.
- Facilitate platform upgrades and cloud migration of data assets and pipelines.
- Provide both technical and business support for the development of new platforms and tools for data science, utilizing both on-premises and cloud technologies.
- Identify, design, and implement internal process improvements to enhance scalability for existing client solutions.
- Engage with broader business stakeholders to assist clients and consultants with their data and infrastructure requirements.
- Partner with Technology during the quarterly planning cycle and support management with relevant metrics to assess performance, stability, and reliability of various tools.
- Continuously strive to improve infrastructure efficiency by analyzing query logs, tuning settings, and optimizing queries as needed.
- Review scripts for best practices, providing education to users and developing training materials for beginners and intermediate users.
- Enhance consistency of tool usage by creating guidance for specific data science applications and sharing it with the user community.
This position offers a hybrid work environment, allowing for a blend of remote and in-office collaboration.

