Senior Data Engineer

Mastercard; Malahide; On-site; EUR 100,000 - 130,000; Full time

Job summary

Mastercard is seeking a Senior Data Engineer to design, build, and operate cloud-native data products within the Data Commercialization Platform. You will develop scalable batch and streaming pipelines, implement governance and security controls, and contribute to platform modernization and CI/CD practices.

You will collaborate with product, architecture, and business teams to deliver enterprise data solutions, participate in production support, and help drive architectural excellence in a

Qualifications

• Bachelor's degree in a technical field (CS, Engineering, IS, Math, or related).
• Experience designing, developing, and supporting large-scale data engineering and platform engineering solutions.
• Hands-on with Databricks, Snowflake, Iceberg, Delta Lake, and AWS and/or Azure.
• Strong Python, SQL, Spark/PySpark, and data engineering best practices.
• Experience building batch and real-time data processing pipelines.
• Experience with orchestration/workflow tools (e.g., Airflow).
• Experience with CI/CD, Git, automated testing, IaC, and production support.
• Understanding of data governance, security controls, data quality, metadata, and lineage.
• Strong analytical, problem-solving, communication, and collaboration skills.

Responsibilities

• 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.

Skills

Python

SQL

Spark/PySpark

CI/CD

Airflow

Data governance

Communication

Collaboration

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, or related field

Tools

Databricks

Snowflake

Apache Iceberg

Delta Lake

AWS

Azure

Job description

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.