Analyst, Information Consumption

 Visas future is powered by data. Our ability to responsibly harness data will shape our strategies products policies and longterm growth. As part of this mission Visa is accelerating its datadriven capabilities with a bold vision led by Visas first Chief Data Officer and the Global Data Office (GDO). The GDO leads highimpact companywide initiatives in data strategy data investments policy development and marketplace executionworking closely with Technology Privacy and all global lines of business. We are committed to advancing innovation while upholding Visas Data Values and ensuring trusted privacycentric use of data worldwide.

Within the Global Data Office the Information Consumption Product Team is responsible for building optimizing and scaling Visas unified data platformthe foundation that powers analytics AI/ML decisioning systems and datadriven products across the organization. Our team partners with engineering product and business stakeholders to deliver secure scalable highquality capabilities that support internal and external data consumers.

As a Analyst (Data Engineering) you will play a pivotal role in shaping the nextgeneration data foundation that fuels secure collaboration analytics and innovation at Visa. You will bridge product strategy with technical execution ensuring that platform capabilities align with business needs while meeting high standards for security privacy and regulatory compliance. This role offers the opportunity to influence Visas global datasharing strategy support privacycentric collaboration and drive adoption of cloudnative and generative AIenabled data engineering practices.

Key Responsibilities:

• Translate business and product requirements into scalable secure data engineering solutions across cloud and hybrid environments.
• Design and implement data ingestion transformation sharing and quality pipelines leveraging cloudnative platforms.
• Build and scale data clean room capabilities that enable multiparty collaboration while meeting privacy governance and regulatory needs.
• Develop reusable data services APIs and frameworks that enable unified data access across cloud and onpremise systems.
• Optimize platform performance storage compute and datatransfer efficiency across distributed systems.
• Implement and maintain robust data security governance access controls and compliance frameworks.
• Partner with data scientists product managers business engineers architects and analytics teams to deliver dataasaservice (DaaS) capabilities.
• Lead the modernization of legacy Hadoop pipelines and datasets into cloudnative architectures.
• Provide mentorship on data engineering standards design principles quality frameworks and best practices.
• Apply Generative AI (GenAI) to automate code development documentation pipeline optimization and data lifecycle workflows. 

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications :

Basic Qualifications:
Bachelors degree in Computer Science Data Analytics Data Engineering or a related technical field with 4 years of relevant experience

Preferred Qualifications:
Technical Expertise
4 years of professional experience with a Bachelors degree in Computer Science Data Engineering Analytics or similar.
Strong handson experience (3 years) in data engineering with the ability to support product analytics workflows and collaborate closely with product teams.
Proficiency in distributed data processing technologies such as Apache Spark Hadoop and modern data engineering languages (Python SQL Pandas PySpark).
Experience supporting or building secure data collaboration solutionsData Clean Rooms privacypreserving sharing governance frameworks and controlled dataaccess models.
Skilled in ETL/ELT development workflow orchestration (Airflow Dagster Prefect) and distributed query engines (Presto Trino Drill Athena).
Strong understanding of cloudnative data architecture (AWS Azure or GCP)object storage compute frameworks data lake/lakehouse patterns Delta Sharing IAM encryption.
Familiarity with synthetic data generation ML workflows and model lifecycle considerations.
Advanced cloud certifications (AWS Databricks Snowflake etc.) are a plus.

Product & Domain Knowledge:
Experience collaborating with product managers analysts and engineering teams to deliver scalable insightdriven data products.
Understanding of payments financial data ecosystems and regulatory requirements prior domain experience is strongly preferred.
Strong command of data privacy compliance standards (PCI GDPR) and secure dataaccess patterns.
Ability to translate ambiguous or evolving business needs into clear technical requirements and influence product direction using a datafirst perspective.

Collaboration & Leadership:
Experience working in agile environments driving crossfunctional alignment across engineering analytics product compliance and business stakeholders.
Excellent communication skills with the ability to present tradeoffs guide datadriven decisions and support product planning.
Proven ability to design and support robust reliable and scalable data solutions especially for highvolume transactional or analytics platforms.
Creative structured problemsolver with the ability to operate in ambiguous environments and propose innovative datadriven solutions.

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