Mastercard

8 hours ago

Lead Data Engineer, Data Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Build and scale data unification capabilities that provide a single, unified view across multiple sources, enabling real-time, data-driven cyber products and actionable insights. Lead data ingestion, aggregation, processing, and analytics for high-volume transaction and product datasets. Partner with Product Management, Data Science, Platform Strategy, and Technology to deliver data solutions, prototypes/POCs, and custom reporting. Work with Python (Pandas, NumPy, PySpark, Impala), SQL, Hadoop, Cloudera, Databricks, and AWS.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Perform data ingestion, aggregation, and processing to enable insights from available datasets.
•Leverage platform capabilities including Cloudera Data Engineering (CDE), Cloudera AI (CAI), Databricks, and AWS to deliver data engineering solutions.
•Partner with Product Management, Data Science, Platform Strategy, and Technology teams to address data needs and deliver business-value data solutions.
•Analyze complex, high-volume, high-dimensional data from multiple sources to generate actionable recommendations and insights.
•Identify innovative ideas and deliver proofs of concept/prototypes, integrate new data assets, and support product enhancements through feedback synthesis.

Key Requirements

•Good understanding of Python, including Pandas, NumPy, PySpark, and Impala.
•Experience performing data analysis, development, and testing on Hadoop and the Databricks cloud platform.
•Strong SQL plus higher-level programming languages, with knowledge of data mining and machine learning algorithms and tools.
•Hands-on experience with data modeling, programming, querying, data mining, and report development for business intelligence and custom reporting.
•Experience with ETL/ELT tools such as Apache NiFi, Azure Data Factory, Pentaho, or Talend (good to have).

Skills:CommunicationCollaborationProblem-solving

Tech Stack:PythonPandasNumPyPySparkImpalaSQLHadoopDatabricksCloudera Data Engineering (CDE)Cloudera AI (CAI)AWSETLELTApache NiFiAzure Data FactoryPentahoTalendGraph DatabaseData modelingData visualization

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

8 hours ago

Lead Data Engineer, Data Engineering

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Perform data ingestion, aggregation, and processing to enable insights from available datasets.
•Leverage platform capabilities including Cloudera Data Engineering (CDE), Cloudera AI (CAI), Databricks, and AWS to deliver data engineering solutions.
•Partner with Product Management, Data Science, Platform Strategy, and Technology teams to address data needs and deliver business-value data solutions.
•Analyze complex, high-volume, high-dimensional data from multiple sources to generate actionable recommendations and insights.
•Identify innovative ideas and deliver proofs of concept/prototypes, integrate new data assets, and support product enhancements through feedback synthesis.

Key Requirements

•Good understanding of Python, including Pandas, NumPy, PySpark, and Impala.
•Experience performing data analysis, development, and testing on Hadoop and the Databricks cloud platform.
•Strong SQL plus higher-level programming languages, with knowledge of data mining and machine learning algorithms and tools.
•Hands-on experience with data modeling, programming, querying, data mining, and report development for business intelligence and custom reporting.
•Experience with ETL/ELT tools such as Apache NiFi, Azure Data Factory, Pentaho, or Talend (good to have).

Skills:CommunicationCollaborationProblem-solving

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