4 days ago

Principal Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Steer and implement Big Data initiatives for the GBSC Tech team across Mastercard’s cloud and on-prem ecosystem. Serve as a subject matter expert in data engineering, designing and building scalable data pipelines, storage schemas, and ingestion/transformation/consumption architectures. Define reference architectures and standards, stay current on data platforms (e.g., Azure Data Fabric, Cloudera, Databricks, Apache Ozone, AWS S3), ensure governance/security/privacy alignment, and mentor teammates while collaborating across time zones.

Location: Pune

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Sr. Manager level

Key Responsibilities

•Act as the GBSC subject matter expert (SME) for data engineering best practices and solution design.
•Design and build scalable data pipelines and data storage schemas across Mastercard’s evolving on-prem and cloud ecosystem.
•Define and evangelize reference architectures, design patterns, and engineering standards for ingestion, transformation, storage, and consumption.
•Translate data needs into scalable, ingestible storage and schema solutions in collaboration with stakeholders.
•Mentor team members and lead execution across time zones while aligning solutions with governance, security, privacy, and compliance standards by design.

Key Requirements

•Demonstrated experience designing and building end-to-end data pipelines using ETL/ELT patterns.
•Hands-on experience with data lake, lake house, and/or data warehouse architectures, including schema design and performance optimization.
•Strong data modeling knowledge (dimensional, normalized, and analytical models).
•Advanced SQL expertise, including performance tuning for very large and complex datasets.
•Expert proficiency in Python or Java (or equivalent) for building production-grade data systems, plus distributed processing experience (e.g., Apache Spark).

Experience:Financial servicesPaymentsHigh reliability

Skills:AnalyticsAttention to detailAutomation mindsetLeadershipCommunication

Tech Stack:PythonJavaSQLETLELTData pipelinesData lakeLakehouseData warehouseData modelingDimensional modelingNormalized modelingAnalytical modelsApache SparkAzure Data FabricDatabricksClouderaApache OzoneAWS S3

Company Brief

Mastercard

Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Mastercard

4 days ago

Principal Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: Pune

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Sr. Manager level

Key Responsibilities

•Act as the GBSC subject matter expert (SME) for data engineering best practices and solution design.
•Design and build scalable data pipelines and data storage schemas across Mastercard’s evolving on-prem and cloud ecosystem.
•Define and evangelize reference architectures, design patterns, and engineering standards for ingestion, transformation, storage, and consumption.
•Translate data needs into scalable, ingestible storage and schema solutions in collaboration with stakeholders.
•Mentor team members and lead execution across time zones while aligning solutions with governance, security, privacy, and compliance standards by design.

Key Requirements

•Demonstrated experience designing and building end-to-end data pipelines using ETL/ELT patterns.
•Hands-on experience with data lake, lake house, and/or data warehouse architectures, including schema design and performance optimization.
•Strong data modeling knowledge (dimensional, normalized, and analytical models).
•Advanced SQL expertise, including performance tuning for very large and complex datasets.
•Expert proficiency in Python or Java (or equivalent) for building production-grade data systems, plus distributed processing experience (e.g., Apache Spark).

Experience:Financial servicesPaymentsHigh reliability

Skills:AnalyticsAttention to detailAutomation mindsetLeadershipCommunication

Company Brief

Mastercard

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor