Cloud Data Engineering Lead

5 days ago

O'Fallon, United States MasterCard Full time

Job Title: Cloud Data Engineering Lead

Job Summary:

We are seeking a highly skilled Cloud Data Engineering Lead to drive Predictive and Prescriptive Analytics solutions for our Loyalty Rewards & Segments Program. The successful candidate will design and implement new data pipelines, transfers, and compliance infrastructure to support cloud-based data usage.

Responsibilities:

  • Design and implement new data pipelines, transfers, and compliance infrastructure to support cloud-based data usage.
  • Lead data modernization and transformation initiatives for Loyalty Data products, ensuring compliance with regulations like PCI-DSS, GDPR, and On-Soil requirements.
  • Identify and develop cloud-native solutions for evolving data-related product requirements.
  • Build solutions on cloud data platforms, such as Databricks, following industry standards.
  • Collaborate with architects, technical leads, and DBAs to develop data pipelines.
  • Stay current with emerging trends in big data and cloud platforms, providing technical leadership to improve Advanced Analytics Platform.
  • Work with cross-functional agile teams, including Developers, BI Developers, and Product Owners.
  • Collaborate with Product Owners to implement cloud use cases effectively.
  • Participate in architectural discussions, iteration planning, and feature sizing.
  • Follow Agile processes and contribute to Agile ceremonies.

About You:

The ideal candidate is passionate about solving complex problems with elegant solutions and has experience improving processes to boost efficiency. You should have a proven track record of leading technology transformations for large, legacy platforms and guiding the migration from on-premises systems to the cloud. Experience in navigating industry standards (e.g., PCI-DSS), data privacy regulations (e.g., GDPR), and security policies is essential.

Requirements:

  • Data platform engineering concepts, architecture design patterns, and industry best practices.
  • Cloud data platforms like Databricks.
  • Cloud infrastructure, particularly AWS and/or Azure.
  • Expert in data engineering techniques.
  • Proficiency in Python, Scala, Spark, Hadoop platforms and tools (Hive, Impala, Airflow, NiFi, Sqoop), and SQL to build Big Data products and platforms.
  • Developing and deploying production-level data applications and workflows/pipelines, including machine learning systems in Java, Scala, or Python, with full lifecycle involvement—from data ingestion to feature engineering, modeling, and evaluation.
  • Designing scalable data migration solutions using cloud and data lake technologies, along with data transformation tools like Airflow and NiFi for data pipeline orchestration and SQL Server SSIS for ETL.
  • Cloud security models, encryption strategies, and network layers for hybrid on-prem and cloud environments.
  • Curiosity, creativity, and enthusiasm for technology and innovation.
  • Strong quantitative and problem-solving skills.
  • An ability to multitask with attention to detail.
  • Self-motivation, flexibility, and independence in managing your workload.

Location: This is a hybrid position based in Mastercard's O'Fallon, Missouri location.

Equal Opportunity Employer: Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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