Mastercard is hiring a Senior Data Engineer to join our Data Analytics and AI Solutions (DAAI) program. You will be instrumental in building and enhancing an Analytic Foundation suite of commercialized capabilities and a comprehensive data platform. In this role, you will lead technical design and development, partner directly with business areas to build solutions that drive customer value, and contribute as a key member of small, flexible agile teams.
What You'll Do
- Play a large role in the implementation of complex features.
- Lead collaboration with data scientists to understand existing modeling pipelines and identify optimization opportunities.
- Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling.
- Push the boundaries of analytics and powerful, scalable applications.
- Design and develop data pipelines to automate repetitive tasks within data science and data engineering.
- Demonstrate experience leading cross-functional teams or working across different teams to solve complex problems.
- Identify patterns and innovative solutions in existing spaces, consistently seeking opportunities to simplify, automate tasks, and build reusable components for multiple use cases and teams.
- Create data products that are well-modeled, thoroughly documented, and easy to understand and maintain.
- 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 new modules and features.
- Collaborate across teams with exceptional peers who are passionate about what they do.
What We're Looking For
- 5-8 years of overall career experience in engineering, primarily in Data Engineering in an agile production environment.
- High proficiency in using Python or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Oozie, Airflow, NiFi, Scoop), SQL to build Big Data products & platforms.
- Extensive experience with the Spark Processing engine.
- Proficiency in, at least, one modern programming language such as Python, Java or Scala.
- Strong Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.
- Ability to easily move between business, data management, and technical teams; ability to quickly intuit the business use case and identify technical solutions to enable it.
- Working Knowledge in Software Development engineering Paradigms along with Data Engineering.
- Relational Databases as well as NoSQL experience.
- Experience in cloud technologies like Databricks/AWS/Azure.
- Basic Shell scripting and knowledge of Linux/Unix systems.
- Experience in designing & developing software at scale.
- Strong written and verbal English communication skills.
- Motivation, creativity, self-direction, and desire to thrive on small project teams.
- Superior academic record with a degree in Computer Science or related technical field.
Technical Stack
- Languages: Python, Scala, Java, SQL, Shell scripting
- Big Data Platforms: Spark, Hadoop, Hive, Impala, Oozie, Airflow, NiFi, Scoop
- Cloud Technologies: Databricks, AWS, Azure
- Operating Systems: Linux/Unix
Team & Environment
Engineers work in small, flexible agile teams. Every team member contributes to designing, building, and testing features. There are no rigid organizational structures, and each team uses processes that work best for its members and projects.
Company Culture
We believe 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.
