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Data Engineer - Informatica BDM

5 - 10 years

15 - 27 Lacs

Posted:6 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Job Summary

We are seeking a highly motivated Senior Data Engineer with expertise in designing, building, and securing data systems. The ideal candidate will have a strong background in data engineering, security compliance, and distributed systems, with a focus on ensuring adherence to industry standards and regulatory requirements.

Location: Bangalore

Experience: 4 to 13 Years

Must Have: Informatica BDM, Oozie Scheduling, Hive, HDFS

Key Responsibilities

  • Design, implement, and maintain secure data systems, including wrapper solutions for components with minimal security controls, ensuring compliance with bank standards.
  • Identify security design gaps in existing and proposed architectures and recommend enhancements to strengthen system resilience.
  • Develop and enforce security controls for data transfers, including CRON, ETLs, and JDBC-ODBC scripts.
  • Ensure compliance with data sensitivity standards, such as avoiding storage of card numbers or PII in logs, and maintaining data integrity.
  • Collaborate on distributed systems, focusing on resiliency, monitoring, and troubleshooting in production environments.
  • Work with Agile/DevOps practices, CI/CD pipelines (GitHub, Jenkins), and scripting tools to optimize data workflows.
  • Troubleshoot and resolve issues in large-scale data infrastructures, including SQL/NoSQL databases, HDFS, Hive, and HQL.

Requirements

  • Extensive knowledge of Oozie scheduling, HQL, Hive, HDFS, and data partitioning.
  • Proficiency in SQL and NoSQL databases, along with Linux OS configuration and shell scripting.
  • Strong understanding of networking concepts (DNS, Proxy, ACL, Policy) and data transfer security.
  • In-depth knowledge of compliance and regulatory requirements (encryption, anonymization, policy controls).
  • Familiarity with Agile/DevOps, CI/CD, and distributed systems monitoring.
  • Ability to address data sensitivity concerns in logging, events, and in-memory storage.

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