Lead Data Engineer

Job Title: Mastercard Recruitment – Lead Data Engineer

Company Name: Mastercard

Role: Lead Data Engineer

Job ID / Requisition ID: R-292041

Department / Category: AI & Data

Employment Type: Full-Time (Regular)

Experience Level: 8+ Years

Job Location: Hyderabad, Telangana, India (PIN: 500043)

Work Mode: Hybrid / In-Office

Company Overview:

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with its customers, Mastercard is helping build a sustainable economy where everyone can prosper. As a global technology company in the payments industry, Mastercard's mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.

Role Summary / Purpose:

Mastercard is seeking a Lead Data Engineer to join the team in Hyderabad. This is a senior individual-contributor and technical leadership role that drives design standards and guides a team's engineering practices. You will set the technical bar for how Mastercard builds and operates data platforms at scale, balancing hands-on architecture with team leadership. Working in small, agile teams focused on the high-growth fintech marketplace, you will collaborate across functional teams to execute enterprise cloud and data strategies.

Key Responsibilities:

Set and enforce design standards, architectural patterns, and best practices for data pipelines built on Databricks, Apache Spark, Python, PySpark, and dbt.

Provide technical leadership, architectural guidance, and direction to a team of data engineers, owning technical design reviews.

Lead the design and implementation of CI/CD pipelines (GitLab, Jenkins), DataOps automation, and data observability strategies for the team.

Own Databricks platform administration standards and deployment governance using Databricks Asset Bundles (DABs).

Drive the resolution of complex, high-impact technical challenges across data pipelines and underlying data platforms.

Mentor and grow engineers, establishing a high bar for code quality, automated testing, and peer reviews.

Partner closely with Product Managers and business stakeholders on technical roadmaps, feature prioritization, and engineering trade-offs.

Own the deployment, migration, and upgrade strategy for the team's data platforms and cloud environments.

Eligibility Criteria & Qualifications:

Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Quantitative Science, or a related technical discipline.

Experience: 8+ years of proven data engineering experience, including demonstrated technical leadership and architectural ownership.

Location Requirement: Role based out of Mastercard's technology center in Hyderabad, India.

Required Skills & Technical Competencies:

Big Data & Processing Engines: Expert hands-on experience with Databricks (including workspace/cluster administration), Apache Spark, and PySpark.

Programming Languages: Advanced proficiency in Python for distributed data processing and data modeling.

Data Transformation & Testing: Deep expertise in dbt (data build tool), Test-Driven Development (TDD), and data quality validation frameworks.

CI/CD & DataOps: Strong mastery of modern CI/CD tools (GitLab, Jenkins), version control (Git), and automated deployment workflows.

Platform Architecture & Governance: Proven track record defining engineering standards, data observability, performance tuning, and cloud cost optimization.

Leadership & Stakeholder Management: Excellent verbal and written communication skills with the ability to bridge technical architecture with business strategy.

Preferred / Good to Have:

Domain experience in banking, e-commerce, credit cards, or digital payment processing.

Exposure to hybrid environments spanning both SaaS and premises-based architectures.

Certified Databricks Data Engineer Professional or relevant Cloud certifications (AWS / Azure / GCP).