Sr Data Engineer at Visa

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 Senior 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 design and implement large-scale data pipelines and integrated data solutions using the latest technologies, ensuring efficient data storage, processing, and presentation. 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: • Experience in Requirement Gathering, Estimating, Managing large scale Data Engineering Projects.  • Requirement Analysis: Understand and translate business needs into data models supporting long-term solutions.  • Data Modeling: Work with the Business team to implement data strategies, build data flows and develop conceptual data models.  • Data Pipeline Design: Create robust and scalable data pipelines and data products in a variety of domains.  • Data Integration: Develop and maintain data lakes by acquiring data from primary and secondary sources and build scripts that will make our data evaluation process more flexible or scalable across data sets.  • Testing: Define and manage the data load procedures to reject or discard datasets or data points that do not meet the defined business rules and quality thresholds.  • Operations: Able to independently manage the data load operations of the solutions or products in scope and be able to debug, manage stakeholder communications and provide clarification on the data produced.  • Understanding of and ability to Implement Data Engineering principles and best practices.  • Team Leadership: Lead and mentor a team of data engineers. Coordinate with other teams to manage and prioritize work packets.   • Stakeholder Management: Collaborate with stakeholders across the organization to understand their data needs and deliver solutions.  • Continuous Integration and Continuous Deployment (CI/CD): Implement and maintain CI/CD pipelines for data solutions, ensuring rapid, reliable, and streamlined updates to the data environment.  • Leverage AI on day to day tasks to bring in efficiency in implementation and quicker time to market. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.