Senior Data Engineer

Mastercard

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
O'Fallon, MO
Salary
$115,000–$184,000 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $169k
This role $150k
$104k most similar roles pay here $220k

This role pays less than 66% of similar roles. Most pay $137,350–$199,700 — the shaded band above. At the midpoint, this role pays about $150k versus about $169k 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 131 open roles on FindRole.

Listed pay typically runs $115,000–$184,000 across 118 roles with salary data.

Most-posted roles

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At a glance

TL;DR · Senior Data Engineer

The Senior Data Engineer joins the Data Collection & Engineering organization to design, build, and scale next-generation data platforms and analytical ecosystems. This role involves developing high-performance, cloud-enabled data pipelines for enterprise warehouse and Lakehouse environments to support advanced analytics and regulatory reporting. The engineer will build batch and near-real-time processing frameworks for petabyte-scale workloads while migrating legacy ETL and analytics workloads to cloud-native architectures. Key technical requirements include proficiency in Apache Spark, Java, Scala, Hadoop, and SQL, alongside experience with Amazon S3, EMR, AWS Glue, Apache Airflow, and Apache NiFi. The role also requires expertise in relational and NoSQL databases like Oracle, Cassandra, and DynamoDB. This position addresses the challenge of processing billions of payment events within a global payment processing platform while ensuring security and compliance for sensitive financial data.

What does a Data Engineer earn?

Median $162000 from 191 postings across 57 companies.

See salary data

What you'll do

  • Design and deploy secure, scalable data pipelines using Apache Spark, Java/Scala, and Hadoop.
  • Build batch and near-real-time processing frameworks to support petabyte-scale workloads.
  • Develop reusable engineering components and design patterns to accelerate data product delivery.
  • Implement enterprise capabilities including data lineage, metadata management, quality monitoring, and observability.
  • Migrate legacy ETL and analytics workloads from on-premises environments to cloud-native architectures like AWS.
  • Troubleshoot complex production incidents and perform root cause analysis for sustainable remediation.
  • Mentor junior engineers through code reviews, technical coaching, and knowledge sharing.

What we're looking for

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline (or equivalent practical experience).
  • Experience as a Data Engineer delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
  • Proven experience migrating ETL/ELT, data warehouse, and analytics workloads from on-premises platforms to cloud-native architectures.
  • Strong development experience with Apache Spark, Scala and/or Java, Hadoop ecosystem technologies, and cloud object storage platforms.
  • Experience building orchestration and workflow solutions using Apache Airflow, Apache NiFi, or comparable enterprise scheduling frameworks.
  • Strong SQL expertise and experience working with relational and NoSQL databases such as Oracle, SQL Server, Cassandra, and DynamoDB.
  • Working knowledge of cloud platforms, preferably AWS, including Amazon S3, EMR, and AWS Glue.
  • Strong understanding of security, privacy, regulatory, and compliance requirements for sensitive financial data.

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