# Senior Data Engineer

**Company**: Mastercard
**Location**: Hyderabad, India
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Finance

**Apply**: https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Hyderabad-India/Senior-Data-Engineer_R-291969?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/senior-data-engineer-b261fc5b-d69/

## Description

Mastercard powers the global economy by enabling secure, seamless, and intelligent payments across the world. As a Senior Data Engineer within the Data Collection & Engineering (DC&E) organisation, you will play a critical role in designing, building, and scaling Mastercard's next-generation data platforms and analytical ecosystems.

**Key Responsibilities**

**Data Engineering & Development**

- Design, develop, test, and deploy high-quality, secure, scalable, and resilient data pipelines using Apache Spark, Java/Scala across Hadoop and cloud-native object storage platforms.

- Build and maintain batch and near real-time data processing frameworks capable of supporting petabyte-scale workloads.

- Develop reusable engineering components and frameworks that accelerate data product delivery while maintaining enterprise standards.

**Architecture & Platform Engineering**

- Design and implement a "build once, run anywhere" architecture supporting seamless deployment across on-premises and public cloud environments without code changes.

- Implement data lineage, metadata management, data cataloguing, data quality controls, and observability capabilities across the data ecosystem.

- Collaborate with architects and platform teams to establish scalable design patterns and engineering best practices.

**Cloud Modernisation**

- Contribute to migration initiatives moving legacy ETL and data warehouse workloads from on-premises environments to cloud-native architectures.

- Leverage cloud services such as Amazon S3, EMR, Glue, and related data services to improve scalability, reliability, and operational efficiency.

- Drive adoption of modern lakehouse and distributed compute architectures.

**Delivery & Technical Leadership**

- Lead end-to-end development activities including requirement analysis, solution design, coding, testing, deployment, and production support.

- Mentor and guide junior engineers through code reviews, technical coaching, and engineering best practices.

- Partner with product owners, analysts, architects, and business stakeholders to deliver high-quality solutions within committed timelines.

**Operational Excellence**

- Troubleshoot complex production incidents and perform root cause analysis to identify and implement long-term remediation strategies.

- Ensure compliance with Mastercard's engineering, security, quality assurance, and operational governance standards.

- Continuously identify opportunities to improve performance, automation, monitoring, and process efficiency.

**Innovation**

- Evaluate emerging data technologies and conduct proof-of-concept (POC) initiatives to determine their applicability within Mastercard's data ecosystem.

- Contribute to engineering innovation and continuous improvement initiatives across the organisation.

**Qualifications Required**

- 7+ years of experience delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.

- Proven experience implementing multiple end-to-end data engineering projects within large-scale distributed computing environments.

- Hands-on experience migrating ETL and analytics workloads from on-premises platforms to cloud-native environments.

**Technical Expertise**

- Strong development experience using: Apache Spark, Scala or Java, Hadoop ecosystem technologies, Object Storage platforms.

- Experience building orchestration and workflow solutions using: Apache Airflow/ Apache NiFi and Similar enterprise scheduling frameworks.

- Strong SQL expertise and experience with Relational and NoSQL database technologies: Oracle/ SQL Server, Cassandra, Dynamo DB etc.

- Working knowledge of cloud platforms, preferably AWS: Amazon S3, EMR, AWS Glue, Cloud-native data services.

**Professional Skills**

- Strong analytical and problem-solving capabilities.

- Experience operating within Agile delivery environments.

- Excellent written and verbal communication skills.

- Proven ability to collaborate within geographically distributed and matrix-based teams.

- Self-starter with strong ownership, accountability, and execution focus.

- Ability to learn emerging technologies quickly and apply them effectively to business challenges.

For more fresh new jobs, check out [yubhub.co](https://yubhub.co/).

## Skills

### Required
- Apache Spark
- Scala
- Java
- Hadoop
- Object Storage
- Apache Airflow
- Apache NiFi
- SQL
- Oracle
- SQL Server
- Cassandra
- Dynamo DB
- AWS
- Amazon S3
- EMR
- AWS Glue

---

Source: [Apply at mastercard.wd1.myworkdayjobs.com](https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Hyderabad-India/Senior-Data-Engineer_R-291969?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)