Data Engineer II
Job ID: R-247955
Location: Pune, Maharashtra, India – 411006
Experience Required: 5+ Years
Education: Bachelor’s Degree in Computer Science / Software Engineering / Related Field
Service Line: Software Engineering
Role Overview
As a Data Engineer II within Mastercard’s Data Engineering & Analytics team, you will build and enhance large-scale data solutions to power analytics, products, and decision-making. You will work on complex datasets, build robust pipelines, and collaborate across teams to deliver accurate, scalable, and secure data solutions that enable innovation and actionable insights.
Key Responsibilities
Lead development of scalable data platforms with strong focus on data engineering, quality, and operational efficiency.
Design and maintain high-performance data pipelines, feature stores, analytical and curated datasets.
Tackle multi-layered data complexity and enhance performance of existing frameworks and pipelines.
Monitor and support deployed data applications and identify resolutions to data-related issues.
Ensure data governance practices including lineage, classification, and quality standards.
Integrate diverse data types (batch, real-time, streaming, APIs) into unified data systems.
Experiment with emerging tools to improve development, testing, and deployment processes.
Establish and enforce coding standards, documentation, and data engineering best practices.
Ensure compliance with security and data privacy regulations in all solutions.
Collaborate globally across technical and business teams to deliver high-quality data systems.
Technical Requirements
Strong programming skills in Python and/or Java/Scala.
Experience with big data technologies including Hadoop, Spark, and Kafka.
Proficiency in data orchestration tools such as Apache Airflow or NiFi.
Expertise in SQL performance tuning and optimization of ETL jobs.
Hands-on experience with Agile software development practices.
Skilled in building full data pipelines and machine learning workflows.
Experience with cloud platforms including Azure, AWS, GCP, or Databricks.
Knowledge of data security, data privacy standards, and best practices.
Deep understanding of end-to-end data lifecycle and architecture.
Familiarity with DevOps and CI/CD pipelines for data solutions is a plus.
Preferred Skills
Advanced data troubleshooting and root cause analysis skills.
Strong documentation habits for reproducibility and team sharing.
Prior experience working in distributed global teams.
Effective communicator and collaborator across technical and non-technical teams.
Curiosity and enthusiasm for experimenting with new technologies and frameworks.
