Credit Risk Data Platform Lead

Mastercard Inc.; Dublin; Híbrido; EUR 120 000 - 180 000; Tempo integral

Resumo da oferta

Mastercard Inc. is seeking a Lead Data Engineer for Enterprise Credit Risk to design and scale data platforms supporting credit risk decisioning and analytics.

You will lead enterprise-grade pipelines, implement ETL/ELT with Databricks and Delta Lake, and ensure data quality and governance across cloud data assets. You will partner with Risk, Product, Architecture, and Engineering to translate requirements into scalable data solutions, drive modernization of legacy assets, and mentor engineers

Qualificações

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related STEM field.
• Experience designing large-scale data platforms and data processing systems.
• Knowledge of data quality, governance, metadata practices.

Responsabilidades

• Lead the design, development, and evolution of enterprise-grade data platforms and pipelines.
• Architect and implement scalable ETL/ELT frameworks using Databricks, Spark, Delta Lake, and cloud-native technologies.
• Establish data quality, lineage, governance, observability, and monitoring across data products.
• Drive the migration and modernization of legacy data assets into cloud-based architectures and Data Lakehouse platforms.

Conhecimentos

Databricks

Apache Spark

Delta Lake

SQL

Python

Cloud platforms

ETL/ELT pipelines

Airflow

Data governance

Security & compliance

Formação académica

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

Ferramentas

Databricks

Apache Spark

Hadoop

Delta Lake

SQL

Python

Airflow

Descrição da oferta de emprego

Mastercard Inc. is seeking a Lead Data Engineer for Enterprise Credit Risk to design and scale data platforms supporting credit risk decisioning and analytics.

You will lead enterprise-grade pipelines, implement ETL/ELT with Databricks and Delta Lake, and ensure data quality and governance across cloud data assets. You will partner with Risk, Product, Architecture, and Engineering to translate requirements into scalable data solutions, drive modernization of legacy assets, and mentor engineers