Lead Cloud Data Engineer for AI & Big Data

Mastercard; Portugal; On-site; EUR 85,000 - 130,000; Full time

Job summary

Mastercard is seeking a Lead Cloud Data Engineer to build the next-generation cloud data ecosystem. You will design scalable data solutions on AWS/Databricks, enabling AI-driven insights at global scale and supporting analytics, ML, and business growth.

You will work at the intersection of Cloud, Data Engineering, Analytics and AI, shaping modern data platforms while ensuring security, governance and cost efficiency across enterprise workloads.

Qualifications

• Experience with Big Data technologies including Hadoop and Spark.
• Strong cloud data engineering expertise on AWS and Databricks.
• Proficiency in Python, Java or Scala for data processing.
• Experience building scalable batch/streaming pipelines.
• Familiarity with Lakehouse architectures (Delta Lake, Iceberg).
• Knowledge of data governance, security, and cost optimization.

Responsibilities

• Design, develop and support large-scale cloud-native data solutions on AWS and Databricks.
• Build and maintain batch, streaming, and real-time data pipelines for analytics and ML.
• Engineer scalable distributed data processing systems using Spark and related tech.
• Design modern Lakehouse architectures with Databricks, Delta Lake and Iceberg.
• Lead modernization of data workloads from Hadoop to cloud-native platforms.
• Collaborate with Architects, PMs, Data Scientists and Engineers to implement data solutions.

Skills

Big Data

Hadoop

Spark

Python/Java/Scala

Cloud Architecture

Data Pipelines

Education

BS/MS in Computer Science or related field

Tools

Databricks

Delta Lake

Apache Iceberg

AWS

Apache Spark

Kafka

Job description

Mastercard is seeking a Lead Cloud Data Engineer to build the next-generation cloud data ecosystem. You will design scalable data solutions on AWS/Databricks, enabling AI-driven insights at global scale and supporting analytics, ML, and business growth.

You will work at the intersection of Cloud, Data Engineering, Analytics and AI, shaping modern data platforms while ensuring security, governance and cost efficiency across enterprise workloads.