Senior Data Engineer

Overview

Product Data & Analytics is a centralized global team that enables Mastercard product business units to make better data‑driven decisions. We build internal analytics partnerships that strengthen focus on business performance, portfolio and revenue optimization, initiative tracking, new product development, and go‑to‑market strategies. These capabilities are underpinned by our data platforms that enable insights to be delivered in a standardized, scalable, and cost‑efficient manner.

Key Responsibilities

Strategic Support

• Design and implement value enablement frameworks that optimize pricing strategies, enhance pre-sales propositions, and ensure customer success.

• Collaborate with global and regional teams to tailor solutions that meet regional business needs and align with Mastercard's objectives.

• Provide data-driven insights and recommendations to optimize pricing, pre-sales strategies, and customer success outcomes.

• Develop frameworks, project structures, and presentations to communicate key strategic initiatives.

• Conduct data integrity checks and ensure quality and reliability in data used for analysis.

• Translate complex business problems into analytical solutions that support strategic decision-making.

Technical Leadership

• Lead the development of advanced analytics tools, such as ROI calculators and value dashboards, to measure and optimize business performance.

• Utilize Python, SQL, and BI tools (e.g., Tableau, Power BI) for data analysis, modeling, and visualization.

• Create dynamic, interactive dashboards to provide stakeholders with actionable insights.

• Integrate AI/ML models to enhance the accuracy and efficiency of analytical tools (good-to-have, not mandatory).

• Drive process efficiency and scalability through automation and advanced analytics techniques.

Value Enablement Initiatives

• Develop frameworks for measuring and tracking customer value realization.

• Design predictive models and real-time insights to create tailored customer solutions and business cases.

• Build self-service analytics tools to empower stakeholders with actionable insights.

• Encourage a culture of innovation by promoting participation in Sandbox challenges and regular brainstorming sessions.

• Develop flexible and agile solutions based on a deep understanding of business goals and market context.

Collaboration & Team Enablement

• Collaborate with cross-functional teams to ensure smooth execution of strategic initiatives and projects.

• Foster a collaborative and innovative environment, promoting knowledge sharing and teamwork.

• Lead working sessions to drive alignment and productivity within the team.

• Provide mentorship and feedback to support team members professional development.

• Lead internal training and enablement efforts on analytics tools and methodologies.

Stakeholder Management

• Manage and implement roadmaps for strategic projects, ensuring alignment with business priorities.

• Engage regularly with stakeholders, ensuring effective communication of project progress and addressing escalations.

• Lead standups and project meetings, ensuring clear articulation of agendas, action items, and next steps.

Experience:

• 5+ years of experience in analytics, data science, pricing strategy, customer success, or related fields, ideally within the payments, financial services, or technology sectors (experience in payments industry is a strong plus).

• Proven track record of developing and scaling data-driven tools and frameworks with measurable outcomes.

• Experience in using Python, SQL, and BI tools (e.g., Tableau, Power BI) for building analytics solutions.

• Experience integrating AI/ML models to enhance predictive insights and automate workflows is a good-to-have.

• Proficient in Microsoft Excel and PowerPoint for data analysis, reporting, and presentation development.

Skills

• Strong technical acumen with the ability to design and implement advanced analytics and visualization solutions.

• Exceptional analytical and problem-solving skills, with the ability to derive actionable insights from complex data sets.

• Clear and concise communication skills, with the ability to translate technical insights into business impact for both technical and non-technical stakeholders.

• Ability to work collaboratively within cross-functional teams and promote a knowledge-sharing environment.

• Deep understanding of pricing strategies, customer success enablement, and revenue optimization principles.

Education

• Bachelor's degree in data science, Computer Science, Business Analytics, Economics, Finance, or a related field.

• Advanced degrees (MBA, Master's, or certifications in analytics, data science) are preferred