Mastercard is hiring for Data Engineer

Job Details

1. Company: Mastercard
2. Job Position: Lead Data Engineer
3. Job ID: R-292041
4. Location: Hyderabad, Telangana, India
5. Job Category: AI & Data
6. Job Type: Full-time
7. Experience: 8+ years
8. Qualification: Bachelor’s or Master’s degree in Computer Science or a related technical field
9. Salary: Estimated ₹30 LPA–₹50 LPA
10. Application Deadline: October 30, 2026

Job Overview

Mastercard is hiring a Lead Data Engineer for its AI and Data team in Hyderabad. This senior individual-contributor role combines hands-on data engineering with technical leadership. The selected candidate will design and maintain scalable data platforms using Databricks, Apache Spark, Python, PySpark, and dbt. The role also involves defining engineering standards, managing CI/CD pipelines, improving data observability, and guiding other engineers. Candidates should have at least eight years of data engineering experience and strong expertise in cloud-based data platforms, architecture, and performance optimization.

Key Responsibilities

1. Establish engineering standards and best practices for data pipelines.
2. Design and maintain data solutions using Databricks, Spark, Python, PySpark, and dbt.
3. Provide technical leadership and guidance to data engineers.
4. Lead architecture discussions and design reviews.
5. Develop CI/CD strategies using GitLab and Jenkins.
6. Establish DataOps practices and data observability standards.
7. Define Databricks administration and deployment governance practices.
8. Manage deployments using Databricks Asset Bundles.
9. Troubleshoot complex data pipeline and platform issues.
10. Mentor engineers and promote high-quality coding practices.
11. Conduct code reviews and improve engineering standards.
12. Collaborate with product teams and stakeholders on technical roadmaps.
13. Evaluate technical trade-offs and recommend suitable solutions.
14. Manage data platform deployments, migrations, and upgrades.
15. Improve platform performance, reliability, scalability, and cost efficiency.

Required Skills

1. Databricks development and platform administration.
2. Apache Spark and PySpark.
3. Python programming.
4. dbt and test-driven development (TDD).
5. CI/CD pipelines using GitLab and Jenkins.
6. DataOps and data observability.
7. Data pipeline architecture and optimization.
8. Cloud data platform management.
9. Deployment governance using Databricks Asset Bundles.
10. Code review and engineering quality standards.
11. Performance monitoring and cost optimization.
12. Technical leadership and mentoring.
13. Architecture design and problem-solving.
14. Stakeholder communication and collaboration.
15. Knowledge of banking, e-commerce, credit cards, or payment processing is beneficial.

Why Join Mastercard?

1. Work with a globally recognized payments technology company.
2. Build scalable data platforms supporting global business operations.
3. Gain exposure to modern data engineering technologies.
4. Contribute to cloud transformation and data platform modernization.
5. Take ownership of architecture and engineering standards.
6. Mentor engineers and help improve team performance.
7. Collaborate with product teams and technical stakeholders.
8. Develop expertise in Databricks, Spark, Python, and cloud data engineering.
9. Work on challenging data engineering problems in the financial technology industry.

Important Links

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