Staff Data Engineer (8-10 years' exp - Java/Python, Scala, Spark, Hadoop)

About Us

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

Staff Data Engineers are expert problem-solvers and builders who design, implement, and improve software applications and systems. In this role, engineers spend a significant portion of their time coding, working hands-on with code, data, and modern tools—including AI-assisted development, cloud services, and automation frameworks—to deliver secure, scalable, and high-quality technology solutions that drive business outcomes in the fintech sector. They collaborate with cross-functional teams such as product managers, designers, data scientists, QA, operations, and compliance to translate business requirements into robust technical solutions, all while adhering to best practices, security standards, and regulatory requirements.

This is a hands-on role requiring both deep data engineering expertise and the ability to work across legacy modernization and new platform innovation. You’ll collaborate closely with the Agentic Engineer, ML teams, and business stakeholders to enable AI-driven insights and intelligent data orchestration.

Key Responsibilities:

• Data Platform Modernization: Implement the transition from SQL Server data warehouse to the next-generation Hadoop/Databricks platform, ensuring performance, reliability, and minimal business disruption. Develop hybrid data pipelines that bridge legacy and modern ecosystems, enabling near real-time data access for analytics and AI applications. Optimize existing SQL Server models (facts, dimensions, indexes, stored procedures) and design modern equivalents in Hadoop and Spark environments. Define long-term migration strategy, data partitioning, and retention policies aligned with Visa’s data governance standards.

• Data Architecture & Engineering: Implement scalable, distributed data pipelines using Spark, Kafka, Airflow, and Delta Lake. Build robust ETL/ELT frameworks to process transactional, behavioral, and unstructured data at scale. Partner with the Agentic AI team to power RAG (Retrieval-Augmented Generation) pipelines, vector database integrations and LLM data provisioning. Lead proof-of-concept (POC) initiatives to evaluate and integrate new data engineering technologies.