Lead Data Engineer

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and

Summary:

Lead Data Engineer

Position Title:

Lead Data Engineer

Location:

Austin, TX

Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company.

With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Mastercard's Customer Experience and Disputes team is transforming the post-purchase journey by reducing friction, improving transparency, and enabling real-time collaboration between consumers, merchants, and issuers. This role will contribute to shaping innovative solutions that simplify transaction recognition, enhance purchase management, and streamline dispute resolution.

We are seeking a highly analytical, execution focused, and collaborative Lead Data Engineer to join our Analytics team. This role partners closely with analysts, data engineering teams, and business stakeholders to deliver end-to-end analytical solutions—from designing Snowflake based data models to building Power BI reports and dashboards that support reporting, insights, and ad hoc analysis across the organization.

The role is responsible for developing and optimizing Snowflake tables, views, dynamic tables, and stored procedures using plain SQL, and for designing analytics friendly data models that are performant, trusted, and easy to consume. The position also plays a key role in ensuring data quality and reliability through automated testing, controlled deployments, and disciplined promotion practices across environments.

In addition, this role supports the full analytics lifecycle by developing and maintaining Power BI datasets, reports, dashboards, subscriptions, and refresh workflows, while troubleshooting data or visualization issues that impact business users. This is a high impact individual contributor role within the Analytics team, with direct influence on data trust, analytical efficiency, and business decision making.

• Lead the design and implementation of enterprise-scale, analytics-ready data models in Snowflake, enabling scalable reporting, dashboards, and downstream data consumption.
• Architect, build, and optimize highly scalable, resilient data pipelines across cloud environments (including Azure and Snowflake), ensuring robust data quality, security, and operational stability.
• Own and optimize Jenkins CI/CD pipelines, resolving complex build, deployment, and runtime issues across environments.
• Champion Git Lab and Git best practices, driving high-quality code standards through disciplined version control, code reviews, and collaborative development.
• Lead Snowflake deployment strategies using schema change (or equivalent tooling), ensuring consistent, auditable, and repeatable releases aligned with enterprise platform standards.
• Own the end-to-end promotion lifecycle (dev → test → prod), establishing best practices for release management, governance, and environment stability.
• Design and implement enterprise-grade data quality frameworks to ensure accuracy, completeness, and reliability of critical data assets.
• Develop and maintain Python-based solutions for automation, orchestration, testing, and system integrations at scale.
• Build or support JavaScript-based logic (e.g., Snowflake stored procedures) as required for platform extensibility.
• Provide advanced Power BI support, including Snowflake-backed dataset optimization, report and workspace governance, subscription configuration (including dynamic), and troubleshooting performance and delivery issues.
• Apply ML/AI concepts (feature engineering, model lifecycle, evaluation) to influence data modeling, data platform design, and future-state architecture.
• Lead production support and operational excellence, including incident management, root cause analysis, and proactive issue mitigation for data and pipeline ecosystems.
• Independently deliver complex, high-impact data solutions, demonstrating strong technical judgment, ownership, and execution in a fast-paced, evolving environment.
• Partner…