Senior Data Engineer

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Senior Data Engineer

Senior Data Engineer – Spark / Scala / PySpark

Job Summary

We are looking for a highly skilled Senior Data Engineer with deep expertise in Apache Spark, Scala, and PySpark to build and operate large‑scale batch and streaming data processing systems. The role has a strong emphasis on real‑time streaming architectures using Kafka and Spark Structured Streaming, alongside ingestion and orchestration with Apache NiFi and scalable storage using Apache Ozone and Ceph. This position is ideal for engineers who enjoy solving complex performance, scalability, latency, and reliability challenges in production data platforms.

Key Responsibilities

Design, develop, and maintain large‑scale Spark applications using Scala and PySpark Build and operate streaming‑heavy data pipelines using Kafka and Spark Structured Streaming Implement stateful streaming patterns including windowing, watermarking, late data handling, and checkpointing Develop robust event replay and reprocessing workflows using Kafka offsets and partitions Build ingestion and routing flows using Apache NiFi, including Kafka‑based ingestion patterns Implement end‑to‑end ETL/ELT pipelines with strong emphasis on low latency, fault tolerance, and scalability Optimize Spark jobs through partitioning strategies, memory tuning, shuffle optimization, and efficient data formats Integrate Spark workloads with distributed object storage systems such as Apache Ozone and Ceph Ensure data quality, consistency, and auditability through validation, reconciliation, and metadata capture Collaborate with platform, infrastructure, and operations teams on production readiness and capacity planning Support production systems, including monitoring, incident analysis, and root‑cause resolution Contribute to reusable frameworks, coding standards, and engineering best practices Participate in architecture reviews, code reviews, and technical documentation

Required Qualifications