Senior Data Engineer
Mastercard1 day ago
Base Salary
$115k - $184k/yr
Responsibilities
- Design, develop, test, and deploy secure, scalable, high-performance data pipelines using Apache Spark, Java or Scala, Hadoop, and cloud object storage.
- Build batch and near-real-time data processing frameworks for petabyte-scale workloads.
- Develop reusable engineering components, frameworks, and architecture patterns for data product delivery.
- Design portable architectures deployable across on-premises and public cloud environments without code changes.
- Implement data lineage, metadata management, data cataloging, data quality, monitoring, and observability capabilities.
- Migrate legacy ETL, data warehouse, and analytics workloads to cloud-native architectures using services including Amazon S3, EMR, and AWS Glue.
- Lead requirements analysis, solution design, coding, testing, deployment, production support, and optimization.
- Collaborate with product owners, analysts, architects, platform teams, and business stakeholders to deliver scalable solutions.
- Troubleshoot production incidents, perform root cause analysis, and implement sustainable remediation while meeting security and governance standards.
- Mentor engineers through code reviews, technical coaching, knowledge sharing, and design guidance.
Requirements
- Hands-on experience delivering enterprise-scale data warehouse, data lake, or data Lakehouse solutions as a Data Engineer or Senior Data Engineer.
- Experience delivering multiple end-to-end data engineering initiatives in large-scale distributed computing environments.
- Experience migrating ETL/ELT, data warehouse, and analytics workloads from on-premises platforms to cloud-native architectures.
- Strong experience with Apache Spark, Scala and/or Java, Hadoop ecosystem technologies, and cloud object storage.
- Experience with Apache Airflow, Apache NiFi, or comparable enterprise scheduling and workflow frameworks.
- Strong SQL expertise and experience with relational and NoSQL databases such as Oracle, SQL Server, Cassandra, and DynamoDB.
- Working knowledge of AWS, including Amazon S3, EMR, AWS Glue, and other cloud-native data services.
- Understanding of security, privacy, regulatory, and compliance requirements for sensitive financial and customer data.
- Ability to lead complex technical initiatives across teams and influence engineering direction without direct authority.
- Experience mentoring engineers and providing design guidance, knowledge sharing, and constructive feedback.
- Strong communication and stakeholder management skills for technical and business audiences.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline, or equivalent practical experience.
Benefits
- Hybrid position based in O’Fallon, Missouri, requiring three days per week onsite.
- Full-time benefits generally include medical, prescription drug, dental, vision, disability, and life insurance; flexible spending and health savings accounts; paid leave; 401(k) matching; fitness reimbursement or onsite fitness facilities; and tuition reimbursement.
- Paid leave includes 16 weeks of new parent leave, up to 20 days of bereavement leave, 80 hours of Paid Sick and Safe Time, 25 vacation days, five personal days, and 10 annual paid U.S. holidays.
- Position is intended to be filled by 12/30/2026.
Tech Stack
Amazon DynamoDBApache AirflowApache CassandraApache HadoopApache SparkAWSJavaMicrosoft SQL ServerScalaSQL
Categories
Data Engineering
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).