Data Engineering Specialist

The Data Engineering Specialist is a vital role within our Unified Commerce Platform (UCP) team, responsible for designing, building, and maintaining the data infrastructure that powers our commerce platform! This position requires expertise in creating scalable data pipelines that capture the full spectrum of commerce operations, including subscriptions, usage metering, payment processing, fraud signals, and customer interactions. The ideal candidate will build the foundation that enables both operational excellence and strategic insights across our diverse tenant base, directly impacting revenue assurance and business growth.

What you'll be doing:

• This position involves designing and implementing comprehensive data pipelines that capture the entire commerce lifecycle, from customer acquisition through revenue recognition. It includes building real-time streaming solutions for fraud detection, payment processing, and usage metering, supported by robust monitoring systems to ensure reliability and security.

• A unified data model is developed and maintained to connect customer profiles, subscription states, payment histories, and marketing touchpoints, providing a holistic view of the business. Specialized data structures and processing algorithms are created to support financial reporting, compliance, and revenue forecasting, tailored to the organization's specific needs.

• Sophisticated data enrichment processes are implemented to enhance transactional data with risk scores and customer context, making the data more actionable for downstream systems. Rigorous validation frameworks ensure the integrity of financial data, alongside specialized security controls to protect sensitive information.

• The role also includes integrating UCP data with external systems such as marketing platforms, CRM tools, and financial applications, enabling a comprehensive and connected business view. Additionally, APIs and integration points are developed to expose commerce data to internal tools, dashboards, and partner systems, facilitating data-driven decision-making across the organization.

What we want to see:

• Bachelor's degree in Computer Science, Information Systems, or related technical field (or equivalent experience).

• 5+ years of experience in data engineering with exposure to financial or commerce systems

• Experience building data pipelines for high-transaction environments with strict accuracy requirements

• Familiarity with payment processing systems, fraud detection approaches, or subscription management

• Extensive experience with Apache Spark and Databricks, including optimizing data pipelines, managing cluster configurations, and implementing Delta Lake architecture

• Strong programming skills in Python, R, Java, or Scala

• Expertise with both transactional and analytical database systems

• Experience with cloud-based data platforms (AWS, Azure, or GCP)

• Understanding of financial data compliance requirements (PCI-DSS, SOX, GDPR)

• Knowledge of real-time data processing frameworks for fraud detection and monitoring

Ways to stand out from the crowd:

• Master's degree in a relevant field

• Experience with commerce platforms or payment processing systems or background in financial data engineering, fraud detection systems, or revenue optimization

• Knowledge of machine learning data preparation for predictive analytics

• Experience building data pipelines for marketing attribution or customer journey analysis

• Understanding of data requirements for financial auditing and compliance reporting and/or background integrating multiple data sources for unified customer or transaction views

The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.