Staff Data Engineer

Company Description

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable and secure payments network, enabling individuals, businesses and economies to thrive.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement.

Join Visa: A Network Working for Everyone.

Job Description

This position will be part of VCA (Visa  Consulting & Analytics) function in building and maintaining global data assets and engineering solutions. We are looking expertise in data warehousing and building large-scale data processing systems by using the latest database technologies.  The Data Engineer takes responsibility for building and running data pipelines, designing our local data warehouse and data frameworks, and catering for different data presentation techniques.

Essential Functions

• Exposure working with Global teams & Fortune 500 companies and possess strong experience working directly in client facing roles.
• Execute and manage large scale ETL processes to support development and publishing of reports, Datamart’s and predictive models.
• Strong Data Analytical and Visualization skills along with experience in self-service reporting tools like Tableau or Power BI with KPIs and facilitate Visa Consulting engagements including data exchange.
• Should have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.
• Build ETL pipelines in Spark, Python, HIVE or SAS that process transaction and account level data and standardize data fields across various data sources 
• Build and maintain high performing ETL processes, including data quality and testing aligned across technology, internal reporting and other functional teams
• Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs like performance dashboards, predictive models scoring for client’s deliverables 
• Define and build technical/data documentation and experience with code version control systems (e.g. git). Ensure data accuracy, integrity and consistency
• Find opportunities to create, automate and scale repeatable financial and statistical analysis for Visa Consulting and Analytics.
• Collaborate with Data Engineering teams in North America and other Global regions to production and maintenance of key data assets.
• Strong written, verbal, and interpersonal skills needed to effectively communicate technical insights and recommendations with business customers and leadership team.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

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

• 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
• Strong experience in creating Large scale data engineering pipelines, data-based decision-making and quantitative analysis.
• Advanced experience in writing and optimizing efficient SQL queries with Python, Hive, Scala handling Large Data Sets in Big-Data Environments.  
• Experience with complex, high volume, multi-dimensional data, as well as machine learning models based on unstructured, structured, and streaming datasets.
• Experience with SQL for extracting, aggregating and processing big data Pipelines using Hadoop, EMR & NoSQL Databases.
• Experience creating/supporting production software/systems and a proven track record of identifying and resolving performance bottlenecks for production systems.
• Experience with Unix/Shell or Python scripti