With data being the fuel that drives our future - our strategies, policies, and business successes around data will define our future growth prospects. Unlocking the value available through the innovative use of data on behalf of consumers, businesses, and communities is key to our future. With our ongoing commitment to Visa’s Data Values and the responsible use of data, we at Visa have a bold vision to continue to grow and accelerate our data-related businesses and capabilities.

Led by Visa’s first Chief Data Officer, the Global Data Office coordinates high-impact, complex, company-wide projects related to data business strategy, critical investments, policy development, and marketplace execution. Working closely with Visa’s Chief Privacy Officer, the Technology organization, the wider data community, and the full set of Visa’s global lines of business, the Global Data Office is evolving Visa’s data-related work with momentum and enthusiasm. Driven by its commitment to trusted use of data, Visa is seeking enthusiastic leaders who are change-agents and passionate about the future of data around the world.

About the Team

We are a Data Engineering team within GDO, responsible for designing, building, and optimizing data pipelines and platforms that power Visa’s analytics, and decisioning capabilities. Our focus is on data quality, scalability, and reliability, enabling seamless integration of complex datasets across regions. By partnering with product and business teams, we ensure that data-driven solutions deliver measurable impact and support Visa’s global innovation strategy.

About the role

As a Staff Data Engineer, you will play a critical role in designing and delivering scalable, high-quality data solutions that enable intelligent decision-making across Global Data Engineering capabilities. You will leverage your expertise to architect and implement large-scale data pipelines and modern data warehouse solutions using the latest technologies, ensuring efficient data storage, processing, and presentation.

In addition, you will provide technical leadership and mentoring to data engineering teams, fostering best practices and driving innovation. You will also build and utilize advanced data modeling frameworks and adopt modern architectural patterns such as Medallion Architecture to deliver well-structured, efficient, and future-ready data solutions.

Primary responsibilities

Data Engineering Excellence

• Build and utilize data modeling frameworks and leverage modern architectural patterns such as Medallion Architecture to design scalable, well-structured, and high-performance data solutions.
• Define, execute, and manage large-scale data pipelines to build solutions with required scalability and flexibility for global delivery.
• Build and maintain ETL processes in Spark, Python, and Hive, ensuring data quality, testing, and standardization across multiple sources.
• Develop modular and reusable data pipeline components to reduce code duplication and ensure consistency across projects.
• Enhance pipeline performance and reliability through continuous monitoring, proactive refactoring, and integration of modern frameworks and tools.
• Create and maintain technical/data documentation, including data dictionaries, validation alerts, and code version control (e.g., Git), ensuring data accuracy and integrity.
• Build lightweight visualization dashboards using tools like Tableau or Power BI to support analytical insights.
• Leverage Generative AI (GenAI) to enhance the data engineering lifecycle, including automating code generation, improving documentation, and optimizing pipeline design.

Leadership Skills

• Lead requirement gathering and collaborate with global business and technical teams to ensure smooth solution development, while effectively communicating technical insights and recommendations to stakeholders and leadership.
• Establish and enforce best practices for maintainability and scalability, including coding standards, version control, and automated workflows.
• Provide technical leadership and mentorship to a team of data engineers, promoting best practices and ensuring delivery of high-quality, scalable solutions.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager

Basic Qualifications:
5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD

Preferred Qualifications:
6 or more years of work experience with a Bachelor's Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
Working knowledge of Hadoop ecosystem and associated technologies, (For e.g. Apache Spark, Python, Pandas etc.), Open table formats (e.g. Iceberg)
Big Data Technologies: Advanced experience with Hadoop ecosystem (HDFS, Hive, Spark, EMR). Proficiency in building scalable ETL/data pipelines using tools like Apache Airflow, Oozie, or similar orchestration frameworks
Programming & Scripting: Strong coding skills in Python and SQL for data processing, transformation, and analytics.
Data Architecture & Modeling: Expertise in designing and implementing large-scale, multi-dimensional data architectures. Knowledge of data modeling concepts for both structured and unstructured data.
Data Quality & Governance: Experience implementing data quality frameworks, versioning, and governance practices. Ability to ensure data reliability, integrity, and compliance with internal/external standards.
Data Visualization & Reporting: Proficiency with visualization tools (Tableau, Power BI, D3) for presenting data insights to stakeholders.
Production Systems & Performance Optimization: Experience creating/supporting production-grade software/systems. Proven track record of identifying and resolving performance bottlenecks in data pipelines and systems.
Collaboration & Communication Tools: Familiarity with collaboration platforms (MS Teams, Slack, Confluence, Jira) for stakeholder engagement
Version Control & CI/CD: Experience with code management and version control systems (git). Knowledge of CI/CD pipelines for data engineering and ML workflows
GenAI: Experience in leveraging Generative AI to enhance data engineering workflows
Cloud Platforms: Hands-on experience with cloud data platforms (AWS, Azure) for storage, compute, and data pipeline management.

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.