Data Engineer II, Sustainable Technology

Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title And Summary
Data Engineer II, Sustainable Technology

Who is Mastercard?

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
Are you a skilled and visionary Data Engineer / Scientist with a passion for shaping robust data environments and driving impacts? Join our team at Mastercard and play a pivotal role in defining, building, and optimizing data tools, technologies, and processes.

As the Senior Data Scientist/Engineer, you will spearhead the creation of a reliable and efficient data ecosystem, enabling the delivery of exceptional Data & Analytics Services to both our customers and internal stakeholders.

Role

As the Senior Data Engineer / Scientist for Mastercard's Sustainable Technology, you will be the driving force behind the development and execution of cutting-edge data strategies and data environment frameworks. Your expertise will ensure the effective utilization of data, enabling the delivery of dependable Data & Analytics Services. You will collaborate with cross-functional teams and establish data-related best practices in alignment with Mastercard standards.

Key Responsibilities

• Design, develop, and maintain new data capabilities and infrastructure for Mastercard's Sustainable Technology Internal Data Lake.
• Create new data pipelines, data transfers, and compliance-oriented infrastructure to facilitate seamless data utilization within on-premise/cloud environments.
• Identify existing data capability and infrastructure gaps or opportunities within and across initiatives and provide subject matter expertise in support of remediation.
• Collaborate with technical teams and business stakeholders to understand data requirements and translate them into technical solutions.
• Work with large datasets, ensuring data quality, accuracy, and performance.
• Implement data transformation, integration, and validation processes to support analytics/BI and reporting needs.
• Optimize and fine-tune data pipelines for improved speed, reliability, and efficiency.
• Implement best practices for data storage, retrieval, and archival to ensure data accessibility and security.
• Troubleshoot and resolve data-related issues, collaborating with the team to identify root causes.
• Document data processes, data lineage, and technical specifications for future reference.
• Participate in code reviews, ensuring adherence to coding standards and best practices.
• Collaborate with DevOps teams to automate deployment and monitoring of data pipelines.
• Additional tasks as required.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience as a Data Engineer / Scientist or similar role.
• Deep understanding of data visualization, statistics, hypothesis testing, business intelligence tools, SQL, data cleaning, and data lifecycle management.
• Proficiency in designing and implementing data tools, technologies, and processes.
• Expertise in data engineering, ETL/ELT processes, data warehousing, and data modeling.
• Strong command of data integration techniques and data quality management.
• Hands-on experience with data technologies such as Hadoop, Spark, Python, SQL, Alteryx, NiFi, SSIS, etc.
• Familiarity with cloud platforms and services, such as AWS, GCP, or Azure.
• Excellent problem-solving skills and ability to provide innovative data solutions.
• Strong leadership skills with a proven track record of guiding and mentoring a team.

All About You

• 5–8 years of experience in Data Warehouse-related projects.
• Expertise in Data Engineering and Data Analysis: implementing multiple end-to-end DW projects in Big Data Hadoop environment.
• Experience building data pipelines through Spark with Scala/Python/Java on Hadoop or Object storage.
• Experience working with databases like MS SQL Server, Oracle, and strong SQL knowledge.
• Experience in BI tools like Tableau, Power BI.
• Experience with Alteryx, SSIS, NiFi, Spark, Cloudera Machine Learning, S3 Protocol, PowerBI, NoSQL data structures, Splunk, Databricks, (added advantage)
• Experience automating data flow processes in a Big Data environment.
• Experience working in Agile teams.
• Strong analytical skills required for debugging production issues, providing root cause, and implementing mitigation plans.
• Strong communication skills—both verbal and written—and strong relationship, collaboration, and organizational skills.
• Ability to multi-task across multiple projects, interface with external/internal resources, and provide technical leadership to junior team members.
• Ability to be high-energy, detail-oriented, proactive, and able to function under pressure in an independent environment along with a high degree of initiative and self-motivation to drive results.
• Ability to quickly learn and implement new technologies and perform POC to explore best solutions for problem statements.
• Flexibility to work as a member of a matrix-based diverse and geographically distributed project team.
• Create and maintain a robust data environment that adheres to Mastercard standards and best practices.
• Oversee the management and optimization of data warehouses and data lakes.

Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• 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.