Senior Analyst

Mastercard
Pune, Gurugram
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: ["Problem-solving","Communication","Root-cause analysis","Debugging","Stakeholder collaboration"]

Design, build, and operate scalable data pipelines and curated datasets that power analytics products, reporting, and advanced modeling. Partner with Product, Data Science, and Platform teams to ensure reliability, performance, data quality, and governance across batch and streaming workloads. Build ETL/ELT jobs with PySpark/Spark and SQL, automate data quality and lineage, optimize cost and performance, and support CI/CD, DevOps practices, and on-call operations.

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FursaFursa
Mastercard
Mastercard
1 month ago

Senior Analyst

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Source: Company careers pageValidated by: Fursa AI
Status: Live

Job Summary

Design, build, and operate scalable data pipelines and curated datasets that power analytics products, reporting, and advanced modeling. Partner with Product, Data Science, and Platform teams to ensure reliability, performance, data quality, and governance across batch and streaming workloads. Build ETL/ELT jobs with PySpark/Spark and SQL, automate data quality and lineage, optimize cost and performance, and support CI/CD, DevOps practices, and on-call operations.
Location: Pune, Gurugram
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Build and maintain robust ETL/ELT pipelines for ingestion, transformation, and aggregation of large-scale datasets on Hadoop and enterprise platforms.
  • •Develop high-performance distributed data processing jobs using PySpark/Spark, Python, and SQL (including Impala where applicable).
  • •Translate requirements into reusable, governed data models (facts/dimensions, curated layers, and semantic-ready datasets).
  • •Implement automated data quality checks, reconciliation, lineage documentation, and monitoring to ensure trust in downstream analytics and AI use cases.
  • •Optimize pipeline performance and cost through partitioning, file formats, compute tuning, and efficient query patterns; support CI/CD for data workflows and on-call operations.

Key Requirements

  • •5+ years of relevant experience in data engineering or big data analytics engineering.
  • •Hands-on experience building production-grade data pipelines on big data platforms, including the Hadoop ecosystem (e.g., HDFS, Hive, Impala, YARN, Oozie).
  • •Proficiency in PySpark and Python with strong SQL skills across distributed and relational data stores.
  • •Experience with orchestration/integration tools such as Apache Airflow, Apache NiFi, Azure Data Factory, Pentaho, or Talend.
  • •Bachelor’s degree in computer science, engineering, or equivalent practical experience.
Experience:5+ yearsData engineeringBig data analytics engineeringHadoopCloud data platformsGenAI/LLM
Education:Bachelor's in computer science, Engineering, or equivalent practical experience
Skills:Problem-solvingCommunicationRoot-cause analysisDebuggingStakeholder collaboration
Tech Stack:HadoopHDFSHiveImpalaYARNOoziePySparkSparkPythonSQLApache AirflowApache NiFiAzure Data FactoryPentahoTalendCDCSCD Type 1SCD Type 2ParquetORC

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
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Glassdoor: 4.1
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