Sr. Data Engineer (Big Data & Analytics Engineering)

Mastercard
Pune, Gurugram
Workplace: OnsiteFull timeFunction: Data Analytics & Business IntelligenceExperience: 5+ yearsEducation: bachelorsSkills: ["Problem-solving","Communication"]

Design, build, and operate scalable data pipelines and curated datasets that power analytics products, reporting, and advanced modeling. You’ll develop ETL/ELT workflows on Hadoop and enterprise data platforms, using PySpark/Spark, Python, and SQL, while optimizing performance and cost. Partner with Product, Data Science, and Platform teams to implement governed data models, automate data quality and lineage, and support CI/CD and production reliability, including on-call rotations.

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FursaFursa
Mastercard
Mastercard
1 week ago

Sr. Data Engineer (Big Data & Analytics Engineering)

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Last checked: 3 hours agoStatus: Live

Job Summary

Design, build, and operate scalable data pipelines and curated datasets that power analytics products, reporting, and advanced modeling. You’ll develop ETL/ELT workflows on Hadoop and enterprise data platforms, using PySpark/Spark, Python, and SQL, while optimizing performance and cost. Partner with Product, Data Science, and Platform teams to implement governed data models, automate data quality and lineage, and support CI/CD and production reliability, including on-call rotations.
Location: Pune, Gurugram
Workplace: Onsite
Employment Type: Full time
Job Function: Data Analytics & Business Intelligence
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 data platforms.
  • •Develop high-performance data processing jobs using PySpark/Spark, Python, and SQL (including engines such as 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, monitoring, and data governance (including PII handling, access controls, auditability).
  • •Optimize pipeline performance and cost (partitioning, file formats, compute tuning, caching) and support CI/CD, production troubleshooting, and on-call/operational rotations.

Key Requirements

  • •5+ years of relevant experience in data engineering or big data analytics engineering.
  • •Strong hands-on experience building production-grade pipelines on big data platforms (Hadoop ecosystem such as 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.
  • •Solid understanding of data modeling and incremental processing patterns (CDC, SCD Type 1/2) and building curated datasets for analytics and reporting.
Experience:5+ yearsBig dataData engineeringCloud data platforms
Education:Bachelor's
Skills:Problem-solvingCommunication
Tech Stack:HadoopHDFSHiveImpalaYARNOoziePySparkSparkPythonSQLApache AirflowApache NiFiAzure Data FactoryPentahoTalendETLELTParquetORCDelta Lake

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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