Staff Data Engineer at Visa

Bellevue, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

21 May, 26

Salary

210300.0

Posted On

20 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Hadoop, Apache Spark, PySpark, Scala, Python, SQL, Presto, Trino, Hive, SparkSQL, RDBMS, NoSQL, Data Modeling, ETL/ELT, Databricks, Delta Lake

Industry

IT Services and IT Consulting

Description

Company Description 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 The Staff Data Engineer is a senior technical contributor responsible for designing, optimizing, and scaling key components of Acceptance data platforms across Hadoop and cloud environments. This role delivers high-impact data solutions, drives advanced engineering best practices, and leads technical design for complex initiatives. Staff Engineers act as domain experts, partnering across teams to elevate data architecture, improve reliability, and guide the technical growth of the broader engineering organization. Responsibilities: Architect and implement large-scale data pipelines, ingestion frameworks, and processing systems that support analytics, real-time insights, and enterprise workloads. Lead the design and development of scalable data models, lakehouse structures, and distributed compute solutions across Hadoop and cloud platforms. Provide deep technical guidance during design reviews, code reviews, and architectural discussions, influencing engineering decisions within assigned domains. Build automation frameworks, reusable components, and self-service tooling that improve platform efficiency and reduce operational overhead. Drive platform improvements in data quality, observability, governance, reliability, and performance. Lead multi-team technical projects, collaborating closely with engineering, analytics, and product partners to deliver high-impact data solutions. Evaluate emerging tools and technologies, recommending enhancements that strengthen scalability and data engineering productivity. Mentor Senior and Mid-level Engineers, fostering technical growth and reinforcing engineering best practices. Support strategic initiatives such as cloud migrations, pipeline optimization, data lake/lakehouse modernization, and platform tuning. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager. Qualifications Basic Qualifications: 5+ 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, OR 8+ years of relevant work experience. Preferred Qualifications: Strong expertise with Hadoop and Apache Spark for large-scale distributed data processing. Advanced programming skills in PySpark, Scala, and Python for building production-grade data pipelines. Deep experience with SQL, distributed query engines (Presto, Trino, Hive, SparkSQL), and database/query performance tuning. Hands-on experience with both relational (RDBMS) and NoSQL data systems. Proficiency in data modeling, ETL/ELT design, and data warehousing methodologies. Skilled in architecting cloud-based data solutions on AWS, GCP, and Azure. Advanced proficiency with Databricks, including Delta Lake, job optimization, cluster management, CI/CD, and performance tuning. Ability to lead technical initiatives, mentor engineers, and deliver scalable, reliable data solutions. Strong communication and collaboration skills to work effectively with product, analytics, and engineering partners. Additional Information Work Hours: Varies upon the needs of the department. Travel Requirements: This position requires travel 5-10% of the time. Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. 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. Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code. U.S. APPLICANTS ONLY: The estimated salary range for this position is $131,600 to $210,300 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Job Family Group: Technology and Operations

Responsibilities

The Staff Data Engineer is responsible for architecting and implementing large-scale data pipelines, ingestion frameworks, and processing systems across Hadoop and cloud environments. This role involves leading the design of scalable data models and distributed compute solutions while driving platform improvements in quality, reliability, and performance.