Senior Data Engineer (Data Platforms)-1
Mastercard1 day ago
Pune, IndiaSenior
Responsibilities
- Build the Data Commercialization Platform’s self-service experience and automated control layer.
- Develop end-to-end solutions spanning React web experiences, Java backend services, APIs, data platforms, and cloud infrastructure.
- Provision and govern cloud and lakehouse infrastructure across compute, networking, identity, storage, and security layers.
- Design workflow orchestration platforms and automation frameworks supporting retries, idempotency, reconciliation, and long-running stateful processes.
- Integrate with external systems through APIs and build scalable, secure, observable, and cost-optimized services.
- Contribute to architecture and design discussions and communicate technical trade-offs to engineering, security, platform, and business stakeholders.
- Apply secure coding, access control, automated testing, observability, and troubleshooting across UI, API, data, and cloud layers.
Requirements
- Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
- 6+ years of experience building scalable, reliable data platforms and software in agile environments.
- Experience with distributed systems, microservices, RESTful APIs, modern data and lakehouse platforms, and workflow orchestration.
- Proficiency with Python, Spark or PySpark, Databricks, Unity Catalog, Apache Iceberg or Delta Lake, and Apache Airflow.
- Strong application development experience with Java, Core Java, Spring Boot, React, and TypeScript or JavaScript.
- Hands-on AWS and/or Azure cloud engineering experience including Kubernetes, networking, identity and access management, storage, security, infrastructure as code, observability, and cost optimization.
- Experience with Terraform, CloudFormation, or CDK and cloud delivery practices.
- Experience with relational and NoSQL databases, query optimization, caching, asynchronous processing, and application scalability patterns.
- Experience designing automation frameworks or long-running stateful processes with retries, idempotency, reconciliation, and external integrations.
- Preferred exposure to Kafka, Flink, Trino, EMR, Snowflake, LLM-based applications, retrieval-augmented generation, agentic frameworks, evaluation techniques, and AI coding assistants.
- Ability to evaluate technical trade-offs, participate in architecture discussions, and explain complex solutions to technical and business stakeholders.
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkAWSAzureDatabricksJavaJavaScriptKubernetesPythonReactSnowflakeSpring BootTerraformTypeScript
Categories
BackendData Engineering
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).