Staff Data Engineer, Data Engineering

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 Visas 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 Visas 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 Visas Chief Privacy Officer the Technology organization the wider data community and the full set of Visas global lines of business the Global Data Office is evolving Visas 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 Visas 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 Visas 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

Qualifications :

Basic Qualifications:
5 or more years of relevant work experience with a Bachelors 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 Bachelors 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.

Additional Information :

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.

Remote Work :

No

Employment Type :

Full-time