Lead Data Engineer

Lead Data Engineer

Position Title: Lead Data Engineer

Location: Austin, TX

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.

Overview:

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.

About the Role:

• 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 GitLab 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 cross-functionally with analytics, product, and business stakeholders to enable advanced analytics, refine data definitions, resolve data challenges, and ensure trusted, business-aligned datasets.
• Act as a technical leader and subject matter expert, providing guidance through design reviews, code reviews, and knowledge sharing to elevate engineering standards and drive platform consistency.

All About You:

• Strong background in analytics engineering, data platforms, or data-driven roles supporting enterprise reporting, dashboards, and advanced analytical use cases.
• Deep hands-on Python and SQL with the ability to design, develop, and optimize analytics-ready datasets, strong understanding of relational database concepts, dimensional modeling, and data relationships for scalable analytics consumption.
• Experience working with BI and analytical tools (e.g., Power BI, Excel), with the ability to translate data into actionable insights for business users.
• Proven ability to independently solve complex, end-to-end data and analytical challenges with a strong emphasis on data accuracy, consistency, and quality.
• Strong communication and data storytelling skills, with the ability to clearly articulate data logic, trends, and insights to technical and senior business stakeholders.
• Experience supporting cloud-based analytics platforms (e.g., Snowflake), with familiarity in governance, data quality frameworks, and controlled promotion practices in enterprise environments.
• Experience in payments or financial services is a plus.
• Bachelor's degree in Computer Science or a related field; background in analytics, data science, or other quantitative disciplines preferred.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact View email address on click.appcast.io and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility:

• Abide by Mastercard's security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Pay Ranges:

Austin, Texas: $122,000 - $207,000 USD