Senior Data Engineer

Mastercard is hiring a Senior Data Engineer in Dublin, Ireland. Level rates it ; you can apply on Mastercard.

Level's read on this job

Little AI ●○○○ is how Level rates this data engineer role: aI is not part of the work.
The posting mentions Databricks among its tools and skills.
Level classes it as a senior role.
Mastercard has 923 other open roles on Level.
Posted in the last few days.

AI in this role

Databricks

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.

How we rate this

Senior Data Engineer at Mastercard rates 8 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.