Mastercard
Principal Data Engineer at Mastercard
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Principal Data Engineer
role at
Mastercard .
Overview
Mastercard powers economies and empowers people. We support secure, simple, smart, and accessible payments and build an inclusive digital economy worldwide.
Title and Summary
Principal Data Engineer
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. Our decency quotient (DQ) drives our culture. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Key Responsibilities
Gather and understand the data engineering requirements based on the product and engineering specifications.
Conduct data discovery to build data models, schemas, tables, views, and deployment considerations.
Build appropriate data pipelines to support ETL and automate data workflows.
Build or use existing tools to execute one-time ad-hoc data engineering tasks.
Implement and manage CI/CD pipelines using GitLab and Jenkins, enabling automated testing, deployment, and monitoring of data workflows.
Build fact tables, conduct analysis, and reporting as needs arise.
Conduct data analysis and perform data operations to support business decisions.
Provide architecture guidelines and support from data engineering perspectives in product development.
Apply problem-solving and analytical skills to troubleshoot complex data and system issues.
Support Data Science teams in model deployment and data pipelines.
Document pipeline architecture, processes, and standards to promote consistency and transparency.
Learn latest trends in data engineering and share with the organization; provide thought leadership within the department.
Collaborate with TPMs, product, and stakeholders while executing data engineering assignments by planning with the team.
All About You
Expert in SQL development with hands-on experience in Databricks, Snowflake, Python, and PySpark for designing and implementing data solutions.
Experience collaborating with stakeholders and cross-functional teams to deliver cloud data solutions across Azure, AWS, and data warehouse platforms.
Strong leadership and communication skills to guide data engineering teams and work with both technical and non-technical stakeholders.
Skilled in architecting scalable data models, pipelines, and frameworks leveraging modern cloud data lake architectures.
Experience in planning and executing end-to-end deployments, upgrades, and migrations with best practices for cloud-native and distributed systems.
Bachelor’s degree in Computer Science.
Nice To Have
Understanding of payment networks.
Ability to identify new product ideas from data.
Experience publishing and protecting scientific IP work.
Skills
SQL, Databricks, Azure/AWS, Cloud Data Warehouse, Hadoop, Python, PySpark, NiFi & Data Lake.
Mastercard is an equal opportunity employer. We hire the most qualified candidate for the role and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. US/Canada accommodation requests: reasonable_accommodation@mastercard.com.
Pay Ranges
OFallon, Missouri: USD 138,000 – 221,000
New York City, New York: USD 166,000 – 265,000
Purchase, New York: USD 159,000 – 254,000
Seniorities and Job Type
Seniority level : Mid-Senior level
Employment type : Full-time
Job function : Information Technology
Industries : Financial Services, IT Services and IT Consulting, and Technology
Referrals increase your chances of interviewing at Mastercard. Sign in to set job alerts for “Data Engineer” roles.
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Principal Data Engineer
role at
Mastercard .
Overview
Mastercard powers economies and empowers people. We support secure, simple, smart, and accessible payments and build an inclusive digital economy worldwide.
Title and Summary
Principal Data Engineer
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. Our decency quotient (DQ) drives our culture. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Key Responsibilities
Gather and understand the data engineering requirements based on the product and engineering specifications.
Conduct data discovery to build data models, schemas, tables, views, and deployment considerations.
Build appropriate data pipelines to support ETL and automate data workflows.
Build or use existing tools to execute one-time ad-hoc data engineering tasks.
Implement and manage CI/CD pipelines using GitLab and Jenkins, enabling automated testing, deployment, and monitoring of data workflows.
Build fact tables, conduct analysis, and reporting as needs arise.
Conduct data analysis and perform data operations to support business decisions.
Provide architecture guidelines and support from data engineering perspectives in product development.
Apply problem-solving and analytical skills to troubleshoot complex data and system issues.
Support Data Science teams in model deployment and data pipelines.
Document pipeline architecture, processes, and standards to promote consistency and transparency.
Learn latest trends in data engineering and share with the organization; provide thought leadership within the department.
Collaborate with TPMs, product, and stakeholders while executing data engineering assignments by planning with the team.
All About You
Expert in SQL development with hands-on experience in Databricks, Snowflake, Python, and PySpark for designing and implementing data solutions.
Experience collaborating with stakeholders and cross-functional teams to deliver cloud data solutions across Azure, AWS, and data warehouse platforms.
Strong leadership and communication skills to guide data engineering teams and work with both technical and non-technical stakeholders.
Skilled in architecting scalable data models, pipelines, and frameworks leveraging modern cloud data lake architectures.
Experience in planning and executing end-to-end deployments, upgrades, and migrations with best practices for cloud-native and distributed systems.
Bachelor’s degree in Computer Science.
Nice To Have
Understanding of payment networks.
Ability to identify new product ideas from data.
Experience publishing and protecting scientific IP work.
Skills
SQL, Databricks, Azure/AWS, Cloud Data Warehouse, Hadoop, Python, PySpark, NiFi & Data Lake.
Mastercard is an equal opportunity employer. We hire the most qualified candidate for the role and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. US/Canada accommodation requests: reasonable_accommodation@mastercard.com.
Pay Ranges
OFallon, Missouri: USD 138,000 – 221,000
New York City, New York: USD 166,000 – 265,000
Purchase, New York: USD 159,000 – 254,000
Seniorities and Job Type
Seniority level : Mid-Senior level
Employment type : Full-time
Job function : Information Technology
Industries : Financial Services, IT Services and IT Consulting, and Technology
Referrals increase your chances of interviewing at Mastercard. Sign in to set job alerts for “Data Engineer” roles.
#J-18808-Ljbffr