Lead Data Engineer

Mastercard

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Arlington, VA
Salary
$161,000–$266,000 / yr
Posted
8 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $164k
This role $214k
$110k $283k
below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $126,800–$200,500 — the blue band above. At the midpoint, this role pays about $214k versus about $164k for comparable roles.

Based on 240 similar postings.

Employer

About Mastercard

Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services

Mastercard currently has 150 open roles on FindRole.

Listed pay typically runs $122,000–$207,000 across 142 roles with salary data.

Most-posted roles

View all roles at Mastercard

At a glance

TL;DR · Lead Data Engineer

The Lead Data Engineer joins the Data Commercialization Platform team to design, build, and scale cloud-native data and Business Intelligence solutions. This role involves developing scalable data pipelines, analytics frameworks, and platform capabilities within a modern multi-cloud data ecosystem. The engineer will drive multi-cloud architectures across AWS and Azure, ensuring secure interoperability between Databricks, Snowflake, and various cloud services. Key responsibilities include building CI/CD pipelines, Infrastructure as Code, and automation frameworks while implementing secure access patterns using RBAC and IAM. The position requires deep expertise in Apache Spark, PySpark, Delta Lake, SQL, and Python. The work focuses on solving complex platform requirements by optimizing workloads for performance, reliability, and cost efficiency while establishing engineering standards for development, testing, monitoring, and operational excellence across distributed data solutions.

What you'll do

  • Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS.
  • Build scalable, high-performance data pipelines and analytics frameworks for enterprise data products.
  • Drive the implementation of multi-cloud architectures across AWS and Azure platforms.
  • Build and maintain CI/CD pipelines, automation frameworks, and Infrastructure as Code for platform deployment.
  • Implement secure access patterns using RBAC, IAM, and enterprise identity integration.
  • Optimize data platforms for performance, scalability, reliability, and cost efficiency.
  • Lead technical design reviews and provide mentorship to engineers on complex initiatives.

What we're looking for

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline (equivalent practical experience considered).
  • Deep hands-on experience as a Lead or Senior Data Engineer building enterprise-scale cloud data, analytics, and BI platforms.
  • Strong expertise with Databricks, Snowflake, and AWS services including S3, Glue, EMR, and IAM.
  • Advanced proficiency with Apache Spark/PySpark, Delta Lake, SQL, and Python for large-scale data processing.
  • Experience building scalable ETL/ELT pipelines, data integration frameworks, and distributed data solutions.
  • 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 RBAC, IAM, and data lineage.
  • Experience designing multi-cloud data architectures across AWS and Azure; experience with Azure Databricks and ADLS Gen2 is a plus (preferred).

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