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Mastercard

Processes payments across a global network

Lead Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeArlington County, Arlington, VA, USA

About the Job

Requirements

  • Deep hands-on experience as a Lead or Senior Data Engineer designing and building enterprise-scale cloud data, analytics, and business intelligence platforms.
  • Strong expertise with Databricks, Snowflake, and AWS, including Amazon S3, AWS Glue, Amazon EMR, and AWS Identity and Access Management.
  • Advanced proficiency with Apache Spark and PySpark, Delta Lake, SQL, and Python for large-scale data processing and analytics.
  • Experience building scalable ETL/ELT pipelines, data integration frameworks, and distributed data solutions.
  • Experience designing multi-cloud data architectures and integrations across AWS and Azure.
  • Strong experience with CI/CD, Infrastructure as Code, automation, Git/GitHub, and DevOps practices for data platforms.
  • Experience implementing enterprise security, governance, and access controls, including role-based access control, IAM, service principals, data lineage, metadata management, and observability.
  • Knowledge of modern and open data architectures and formats, including Delta Lake and Apache Iceberg.
  • Understanding of FinOps, cloud cost optimization, performance, and scalability for large-scale data workloads.
  • Proven ability to lead technical design and architecture decisions, drive complex engineering initiatives across teams, and mentor engineers.
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline; equivalent practical experience will also be considered.
  • Strong communication and stakeholder management skills, including the ability to articulate technical decisions, trade-offs, risks, and recommendations.

Responsibilities

  • Design and develop cloud-native data and business intelligence solutions using Databricks and Snowflake on AWS.
  • Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products.
  • Drive implementation of multi-cloud architectures across AWS and Azure, including Azure Databricks and ADLS Gen2.
  • Enable integration and interoperability across Databricks, Snowflake, AWS services, and Azure services.
  • Build and maintain CI/CD pipelines, automation frameworks, and Infrastructure as Code for reliable data platform provisioning and deployment.
  • Implement secure and governed access patterns using role-based access control, IAM, service principals, and enterprise identity integration.
  • Design reusable platform capabilities that enable data interoperability across multiple compute engines and cloud providers.
  • Establish engineering standards for development, testing, deployment, monitoring, documentation, and operational excellence.
  • Optimize data platforms and workloads for performance, scalability, reliability, resiliency, and cost efficiency.
  • Lead technical design reviews and influence architecture and platform engineering decisions.
  • Partner with Product, Architecture, Engineering, Data, and Business teams to translate complex requirements into scalable and sustainable technical solutions.
  • Provide technical leadership and mentorship to engineers while driving initiatives from design through implementation.

Desired Qualifications

  • Experience with Azure Databricks and ADLS Gen2 is a plus.

About the Company

Mastercard

Processes payments across a global network

Mastercard operates a global payment network connecting financial institutions, merchants, businesses and consumers. It authorizes, clears and settles transactions between participating institutions, while banks issue Mastercard-branded cards and extend credit to their customers. Its services also include fraud detection, identity verification, payment tokenization, data analysis and consulting for organizations managing commerce and financial operations. The company earns network fees linked to payment volumes and processed transactions, along with fees for its services and solutions. Founded by a group of banks in 1966, Mastercard is headquartered in Purchase, within Harrison, New York.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Harrison, New York
Founded
1966

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