Dublin 18, Ireland
Live, first seen by us 4 days agoDesign, develop and support cloud-native data products and platform capabilities
Build and operate scalable batch and streaming data pipelines
Develop reusable frameworks, accelerators and platform services
Implement data governance, security, observability and operational controls
Support platform automation through CI/CD and Infrastructure as Code
Design, develop, and support cloud-native data products and platform capabilities.
Build and operate scalable batch and streaming data pipelines.
Develop reusable frameworks, accelerators, and platform services on Databricks, Snowflake, Iceberg, and cloud platforms.
Implement data governance, security, observability, and operational controls.
Support platform modernization, automation, and engineering excellence through CI/CD and Infrastructure as Code.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 4
Early. Similar jobs usually come down between day 6 and day 56.
At Mastercard, jobs usually come down by about day 25.
From 13,743 similar postings that came down, and 268 of Mastercard’s. Coming down is not always a hire.
70 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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The Data Commercialization Platform (DCP) is Mastercard’s cloud-native data and analytics platform focused on building secure, scalable, governed, and reusable data products. The platform leverages Databricks, Snowflake, Apache Iceberg, Delta Lake, and AWS/Azure to enable enterprise data sharing, analytics, AI/ML, and data commercialization capabilities. The role contributes to both data product development and platform engineering, ensuring reliable, secure, and compliant data solutions. Role Design, develop, and support cloud-native data products and platform capabilities. Build and operate scalable batch and streaming data pipelines. Develop reusable frameworks, accelerators, and platform services on Databricks, Snowflake, Iceberg, and cloud platforms. Implement data governance, security, observability, and operational controls. Support platform modernization, automation, and engineering excellence through CI/CD and Infrastructure as Code. Collaborate with product, architecture, platform, governance, and business teams to deliver enterprise data solutions. Participate in production support, operational readiness, and continuous improvement activities. All About You Required Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, or a related technical field. Experience designing, developing, and supporting large-scale data engineering and platform engineering solutions. Hands-on experience with Databricks, Snowflake, Apache Iceberg, Delta Lake, and AWS and/or Azure. Strong proficiency in Python, SQL, Spark/PySpark, and data engineering best practices. Experience building batch and real-time data processing pipelines. Experience with orchestration and workflow automation tools (e.g., Airflow). Experience with CI/CD, Git, automated testing, Infrastructure as Code, and production support. Understanding of data governance, security controls, data quality, metadata, and lineage. Strong analytical, problem-solving, communication, and collaboration skills. Preferred Qualifications Experience with Kafka and event-driven architectures. Experience with Data Contracts, Data Mesh, and data product architectures. Experience supporting AI/ML and advanced analytics workloads. Experience with Terraform and cloud infrastructure automation. Knowledge of enterprise security, IAM, encryption, and privacy controls. Experience working in financial services or other highly regulated industries. 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:
Overview The Data Commercialization Platform (DCP) is Mastercard’s cloud-native data and analytics platform focused on building secure, scalable, governed, and reusable data products. The platform leverages Databricks, Snowflake, Apache Iceberg, Delta Lake, and AWS/Azure to enable enterprise data sharing, analytics, AI/ML, and data commercialization capabilities. The role contributes to both data product development and platform engineering, ensuring reliable, secure, and compliant data solutions. Role Design, develop, and support cloud-native data products and platform capabilities. Build and operate scalable batch and streaming data pipelines. Develop reusable frameworks, accelerators, and platform services on Databricks, Snowflake, Iceberg, and cloud platforms. Implement data governance, security, observability, and operational controls. Support platform modernization, automation, and engineering excellence through CI/CD and Infrastructure as Code. Collaborate with product, architecture, platform, governance, and business teams to deliver enterprise data solutions. Participate in production support, operational readiness, and continuous improvement activities. All About You Required Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, or a related technical field. Experience designing, developing, and supporting large-scale data engineering and platform engineering solutions. Hands-on experience with Databricks, Snowflake, Apache Iceberg, Delta Lake, and AWS and/or Azure. Strong proficiency in Python, SQL, Spark/PySpark, and data engineering best practices. Experience building batch and real-time data processing pipelines. Experience with orchestration and workflow automation tools (e.g., Airflow). Experience with CI/CD, Git, automated testing, Infrastructure as Code, and production support. Understanding of data governance, security controls, data quality, metadata, and lineage. Strong analytical, problem-solving, communication, and collaboration skills. Preferred Qualifications Experience with Kafka and event-driven architectures. Experience with Data Contracts, Data Mesh, and data product architectures. Experience supporting AI/ML and advanced analytics workloads. Experience with Terraform and cloud infrastructure automation. Knowledge of enterprise security, IAM, encryption, and privacy controls. Experience working in financial services or other highly regulated industries. Corporate Security Responsibility
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Yes. We’ve followed 9 other Senior Data Engineer jobs there since May 2026. 2 came down, usually after about 40 days. 7 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
Senior Data EngineerOverviewCorporate 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.
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Dublin 18, Ireland
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.