Senior Data Platform Lead for Credit Risk & Analytics

Mastercard; O’Fallon (MO); Hybride; USD 140 000 - 231 000; Plein temps

Avantages offerts par ce poste

Health insurance

401k with match

Paid time off

On-site fitness facilities

Résumé du poste

Mastercard is seeking a Lead Data Engineer in O'Fallon, Missouri, to design and scale data platforms that support credit risk analytics, decisioning, and regulatory reporting across the ECR portfolio. The role blends hands-on data engineering with technical leadership in cloud environments.

You will mentor engineers, define standards, collaborate with product, risk analytics, data science, and architecture teams, and ensure secure, governance-driven data solutions in a hybrid onsite role.

Qualifications

• Experience designing large-scale data platforms.
• Hands-on with Databricks, Spark, Delta Lake.
• Proficient in SQL and Python for data analytics.
• Cloud data platform experience (Azure/AWS/GCP).
• Strong governance, data quality, and observability practices.

Responsabilités

• Lead the design and evolution of enterprise data platforms.
• Architect scalable ETL/ELT pipelines across cloud data lakes.
• Drive data quality, lineage, governance, and observability.
• Mentor engineers and align solutions with business priorities.

Connaissances

Large-scale data engineering

Distributed data processing

Data governance & quality

Mentoring & leadership

Stakeholder management

Communication

Security & compliance

Java (plus)

Formation

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

Outils

Databricks

Apache Spark/PySpark

Delta Lake

SQL

Python

Azure

AWS

GCP

Airflow

CI/CD tooling

Description du poste

Mastercard is seeking a Lead Data Engineer in O'Fallon, Missouri, to design and scale data platforms that support credit risk analytics, decisioning, and regulatory reporting across the ECR portfolio. The role blends hands-on data engineering with technical leadership in cloud environments.

You will mentor engineers, define standards, collaborate with product, risk analytics, data science, and architecture teams, and ensure secure, governance-driven data solutions in a hybrid onsite role.