Data / ML Engineer II Job in Pune at Mastercard

Mastercard is hiring for the role of Data / ML Engineer - II!

Responsibilities of the Candidates:

• Design and develop data & services products/platforms leveraging data science and engineering.
• Process unstructured data (images, text) for analysis and insights.
• Solve complex problems with multi-layered datasets and optimize machine learning libraries.
• Support deployed data applications and models, guiding data consumers and resolving issues.
• Ensure data governance through data lineage, quality checks, and classification.
• Integrate new data sources (real-time, streaming, batch, API) to enhance insights and testing capabilities.
• Streamline data pipeline development, testing, deployment, and operations.
• Stay updated on technical and product trends through learning, training, and job shadowing.
• Develop data and analytics infrastructure for product development.
• Partner with various teams to identify and solve key business problems.
• Evaluate and select analytics solutions considering usability, feasibility, and stakeholder input.
• Break down solutions into smaller milestones for feedback and iteration.
• Evangelize data product releases, gather feedback, and track usage for future development.
• Collaborate in cross-functional teams to define vision, culture, and processes.
• Prioritize operational activities based on organizational value drivers.
• Escalate technical issues detected during project work.
• Support building scalable machine learning production systems.

Requirements:

• Bachelor's degree in Computer Science, Electrical Engineering, or equivalent is required. (Master's preferred).
• 2+ Years of experience with data pipeline tools (NIFI, Airflow) and automation scripting.
• Experience with Python/Scala, Spark, SQL, and Hadoop for building big data products/platforms.
• Proficiency in software development practices (version control, testing, deployment).
• Basic knowledge of statistical analysis, coding, and data engineering.
• Curiosity, creativity, and passion for technology and innovation.
• Strong quantitative and problem-solving abilities.
• Motivation, flexibility, self-direction, and team player mentality.
• Excellent communication, collaboration, and organizational skills.