Lead Data Engineer

We work 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. Overview: Mastercard is the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Our team within Mastercard – Data & Services: The Data & Services team is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the worlds largest organizations to make multi-million dollar decisions and grow their businesses. The New Product Engineering team within Data and Services is engineering the transformation of new ideas into software solutions to test in the market, and then growing and scaling products to meet long-term demand and needs. We achieve this with a "move fast, learn fast" mindset, relentless focus on customer excellence, and a culture of collaboration and empowerment. Our solutions are instrumental in positioning Mastercard as a data & services market leader. We are looking for an innovative Lead Data Engineer who is passionate about data and analytics, highly motivated and can take technical ownership of data solutions with an emphasis on engineering efficiency and on-time delivery. This individual will partner closely with other areas of the business to build and enhance solutions that drive value for our customers. Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features. The range of work you will encounter varies from designing backend data models, architecting data flows, maintaining the stability of the platform and beyond. The person will get a chance to work with diverse datasets and be on the cutting edge of transforming the way Mastercard captures, processes, stores and visualizes data. As a Lead Data Engineer, you will:

• Provide technical leadership in data architecture, ensuring best practices for data modeling, storage, and retrieval.

• Lead the scoping, design and implementation of complex features including multi-layered data workflows.

• Lead and push the boundaries of analytics and powerful, scalable data workflows and applications.

• Build and maintain data models and data pipelines to enable performant and scalable products.

• Work with multiple sources of data, storage systems, and building processes and pipelines to provide cohesive datasets for analysis and modeling.

• Ensure a high-quality code base by writing and reviewing performant & scalable, well-tested code.

• Collaborate with cross-functional teams to define data requirements and design solutions that align with business objectives.

• Oversee data governance and quality, ensuring data accuracy, consistency, and compliance with industry standards.

• Mentor software engineers & data engineers, establishing data best practices and creating up-skilling opportunities for the team.

• Drive innovative improvements to team development processes.

• Partner with Product Managers and Customer Experience Designers to develop a deep understanding of users and use cases and apply that knowledge to scoping and building features.

• Collaborate across teams with exceptional peers who are passionate about what they do. All about you / Ideal Candidate Qualifications: - 5 years of data engineering experience in an agile production environment.

• Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale.

• Experience leading the design and implementation of complex features.

• Experience leading a large project and working with other data and software engineers.

• Experience working in enterprise databases and ensure follow industry best practices around data privacy.

• Expertise in using Python or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi, Scoop), SQL to build Big Data products & platforms.

• Experience in Java/.net, Scala, or Python technologies and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting.

• Experience in anonymizing data, data product development, analytical models, and AI governance.

• Experience with SQL, Multi-threading, Message Queuing & Distributed Systems.

• Effective communication and collaboration skills to work with both technical and non-technical stakeholders.

• Flexible to work with global offices across several time zones.

• Outstanding problem-solving skills and the ability to navigate complex data challenges. Additional desired skillset:

• Familiarity with industry best practices for collection and use of data.

• Strong technologist eager to learn new technologies and frameworks.

• Project management skills and a demonstrated ability to understand complex information product constructs.

• Knowledge of Splunk or other alerting and monitoring solutions.

• Experience with agile methodologies, DevOps practices, and CI/CD.

• Be able to engage and drive conversations with customers as needed.