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Big Data Engineer

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Hybrid

Big Data Engineer

Bounteous

Big Data Engineer

Skills

SQL QueriesBig DataMongoDBData EngineeringPythonKafkaSnowflakeNeo4jDatabricksData AnalysisAWSLinuxPySparkHadoopAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

10 August 2026

What they need


Senior Data Engineer - Fraud Technology

Location: Bangalore/Hyderabad/Mumbai
Experience: 5-10 Years

Job Summary

We are looking for a Senior Data Engineer to build and maintain scalable data pipelines and data platforms that support Fraud Analytics, Business Intelligence, and Data Science initiatives. The role involves working with large datasets across on-prem and cloud environments using modern data engineering technologies.

Key Responsibilities

  • Develop and maintain data pipelines using Python and PySpark.
  • Build ETL/ELT solutions and data marts for reporting and analytics.
  • Work with SQL Server, Hadoop, and cloud-based data platforms.
  • Optimize and support large-scale data processing workflows.
  • Collaborate with business, analytics, and technology teams.
  • Participate in Agile development and end-to-end project delivery.

Must Have Skills

  • 5+ years of Data Engineering experience.
  • Strong experience in Python and PySpark/Apache Spark.
  • Strong SQL skills.
  • Experience with SQL Server and Hadoop.
  • Experience in ETL/Data Warehousing/Data Marts.
  • Linux and Shell Scripting.
  • Job scheduling tools such as Autosys or Control-M.
  • Good analytical and problem-solving skills.

Good to Have

  • Azure (Databricks, ADF, Synapse, ADLS) or AWS (S3, Glue, Athena).
  • Snowflake.
  • Kafka and Streaming.
  • MongoDB or Neo4j.
  • Data Modeling/Dimensional Modeling.
  • Banking, Fraud, Risk, or Financial Services domain experience.

Keywords

Python, PySpark, Spark, SQL, SQL Server, Hadoop, ETL, Data Warehouse, Data Mart, Linux, Shell Scripting, Autosys, Control-M, Azure Databricks, ADF, AWS Glue, Snowflake, Kafka

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