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Senior Data Engineer

Mastercard Open
Dublin Full-time Senior Data Engineering

At a glance

Senior Data Engineering role at Mastercard. Dublin · full-time.

Pay not stated Data Engineer salary

RoleData Engineering
SenioritySenior
LocationDublin
EmploymentFull-time
PostedNov 10, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build cloud-based data products and platform features, then keep them working reliably
  • Create and run data pipelines for both scheduled batch jobs and streaming workloads
  • Develop shared engineering frameworks and services using Databricks, Snowflake, Iceberg and cloud platforms
  • Put governance, security, monitoring and operational safeguards into data solutions
  • Improve platform delivery with automation, infrastructure as code, production support and cross-team coordination

What you bring

  • A bachelor's degree in a technical discipline such as computer science, engineering or mathematics
  • Experience delivering and supporting data engineering and platform solutions at large scale
  • Practical work with Databricks, Snowflake, Apache Iceberg, Delta Lake and AWS or Azure
  • Strong Python, SQL and Spark or PySpark skills, plus experience creating batch and real-time pipelines
  • Experience with orchestration, CI/CD, Git, testing, infrastructure as code and production support

Who this fits

This senior role suits an engineer who can work across data products and platform engineering, from pipeline delivery to operational support. You’ll collaborate with product, architecture, governance, platform and business teams. The job is based in Dublin, Ireland.

From the employer

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 Engineer

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


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.

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.




Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.