Mastercard Job - 49440010 | CareerArc
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Company: Mastercard
Location: O'Fallon, MO
Career Level: Mid-Senior Level
Industries: Banking, Insurance, Financial Services

Description

Our Purpose

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. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Title and Summary

Senior Data Engineer Overview:
Mastercard's Data Engineering & Analytics team seeks a Senior Data Engineer to develop data & analytics solutions for vast datasets collected from various consumer-focused businesses.
Your role will involve creating high-performance algorithms, cutting-edge analytical techniques, and intuitive workflows to help users derive actionable insights from big data. You will work with large-scale data sets and front-end visualizations to unlock the value of big data and support business needs through innovative data-driven solutions.

Role:
• Drive the evolution of data and services platforms with a strong emphasis on data engineering and data science, ensuring impactful advancements in data quality, scalability, and efficiency.
• Develop and fine-tune methods and algorithms to generate precise, high-quality data at scale, including the creation and maintenance of feature stores, analytical stores and curated datasets for enhanced data integrity and usability.
• Solve complex data challenges involving multi-layered data sets and optimize the performance of existing data pipelines, libraries, and frameworks.
• Provide support for deployed data applications and analytical models, identifying data issues and guiding resolutions.
• Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
• Integrate diverse data sources, including real-time, streaming, batch, and API-based data, to enrich platform insights and drive data-driven decision-making.
• Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
• Collaborate with cross-functional teams to determine priority problems and innovative solutions.
• Develop and enforce best practices for data engineering, including coding standards, code reviews, and documentation.
• Ensure data security and privacy compliance, implementing measures to protect sensitive data.

All About You:
• Bachelor's degree in Computer Science, Software Engineering, or a related field
• Extensive hands-on experience in Data Engineering, including implementing multiple end-to-end data warehouse projects in Big Data environments.
• Proven track record in building and deploying production level data driven applications and data processing workflows/pipelines.
• Proficiency in application development frameworks (Python, Java/Scala) and data processing/storage frameworks (Hadoop, Spark, Kafka).
• Experience in designing and managing data orchestration workflows using tools such as Apache NiFi, Apache Airflow, or similar platforms to automate and streamline data pipelines.
• Experience with performance tuning of database schemas, databases, SQL, ETL jobs, and related scripts.
• Experience of working in Agile teams
• Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale using Java, Scala, or Python. This includes all phases such as data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting analytics.
• Experience in developing integrated cloud applications with services like Azure, Databricks, AWS or GCP.
• Excellent analytical and problem-solving skills, with the ability to analyze complex data issues and develop practical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with and facilitate activities across cross-functional teams, geographically distributed, and stakeholders.

#LI-NF1
#AI3 Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 5 personal days, 10 annual paid U.S. observed holidays, 401k with a best-in-class company match, deferred compensation for eligible roles, fitness reimbursement or on-site fitness facilities, eligibility for tuition reimbursement, gender-inclusive benefits and many more.


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