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

Role Summary

The Staff Data Engineer is a senior technical contributor responsible for designing, building, and scaling reliable data platforms that support analytics, reporting, and ML‑enabled use cases across Visa Direct and related platforms.

This role is data‑engineering led, with additional exposure to Machine Learning workflows, enabling close collaboration with Data Scientists and ML Engineers while ensuring production‑grade data foundations.

Key Responsibilities

• Design, build, and own large‑scale batch and streaming data pipelines using Spark, Kafka, and Python
• Define and maintain robust data models to support analytics, reporting, and ML consumption
• Ensure data quality, reliability, observability, and performance across production pipelines
• Act as a technical lead for complex data initiatives spanning multiple teams
• Partner with Data Science teams to:
• Enable ML feature pipelines
• Support model training and inference data flows
• Operationalize ML outputs into downstream systems
• Drive best practices in data engineering, including code quality, testing, and production readiness
• Mentor engineers and raise overall engineering standards across the data platform
  

Required Skills & Experience

• 8+ years of experience in Data Engineering or Platform Engineering
• Strong hands‑on expertise in:
• Python
• Apache Spark
• Kafka or streaming platforms
• Advanced SQL
• Deep understanding of:
• Distributed data systems
• Data warehousing concepts
• ETL / ELT design patterns
• Experience building and supporting production‑grade data platforms at scale
• Strong problem‑solving skills and ownership mindset
  

Additional / Preferred Skills (ML Exposure)

• Experience supporting Machine Learning pipelines, such as:
• Feature engineering workflows
• Data preparation for model training
• Batch or real‑time inference pipelines
• Familiarity with ML concepts such as:
• Model lifecycle (training, validation, inference)
• Offline vs online features
• Model monitoring inputs/outputs
• Experience collaborating closely with Data Scientists or ML Engineers
• Exposure to ML tooling (e.g., feature stores, model metadata, experimentation frameworks) is a plus (Note: This is not a Data Scientist role; strong data engineering fundamentals are mandatory.)
  

Qualifications

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
• 8+ years of hands‑on experience in Data Engineering, Platform Engineering, or Backend Engineering roles
• Strong proficiency in Python for building data pipelines and production systems
• Extensive experience with distributed data processing frameworks such as Apache Spark
• Hands‑on experience with streaming technologies (e.g., Kafka or similar event‑driven platforms)
• Advanced knowledge of SQL, including complex query optimization and performance tuning
• Solid understanding of data warehousing concepts, data modeling, and ETL/ELT design patterns
• Experience building, deploying, and supporting large‑scale, production‑grade data pipelines
• Strong problem‑solving skills and the ability to operate independently on complex technical problems
  
  

Preferred / Additional Qualifications (Machine Learning Exposure)

• Experience supporting Machine Learning or Data Science workflows, including feature engineering and data preparation
  
  

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.