Senior Software Engineer (Pyspark, Hadoop, Python, SQL, Airflow)

Overview

Senior Software Engineer (Pyspark, Hadoop, Python, SQL, Airflow)

Job Summary

As a Senior Software Engineer focused on Data Quality, you will lead the design, development, and deployment of scalable data quality frameworks and pipelines. You will work closely with data engineers, analysts, and business stakeholders to build robust solutions that validate, monitor, and improve data quality across large-scale distributed systems.

Key Responsibilities

Lead the design and implementation of data quality frameworks and automated validation pipelines using Python, Apache Spark, and Hadoop ecosystem tools.

Develop, deploy, and maintain scalable ETL/ELT workflows using Apache Airflow and Apache NiFi to ensure seamless data ingestion, transformation, and quality checks.

Collaborate with cross-functional teams to understand data quality requirements and translate them into technical solutions.

Define and enforce data quality standards, rules, and monitoring processes.

Perform root cause analysis on data quality issues and implement effective fixes and enhancements.

Mentor and guide junior engineers, conducting code reviews and fostering best practices.

Continuously evaluate and integrate new tools and technologies to enhance data quality capabilities.

Ensure high code quality, performance, and reliability in all data processing pipelines.

Create comprehensive documentation and reports on data quality metrics and system architecture.

Required Skills & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with Data Engineering Experience.
• 5+ years of professional experience in software development, with at least 2 years in a lead or senior engineering role.
• Strong proficiency in Python programming and experience building data processing applications.
• Hands-on expertise with Apache Spark and Hadoop for big data processing.
• Solid experience with workflow orchestration tools like Apache Airflow.
• Experience designing and managing data ingestion and integration pipelines with Apache NiFi.
• Understanding on Data Quality automation, CI/CD, Jenkins, Oracle, Power BI, Splunk
• Deep understanding of data quality concepts, data validation techniques, and distributed data systems.
• Strong problem-solving skills and ability to lead technical discussions.
• Experience with cloud platforms (AWS, GCP, or Azure) is a plus.
• Excellent communication and collaboration skills
  
  
  

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.