Expert Data Transformation Specialist

2 days ago

Bareilly, Uttar Pradesh, India beBeeInformatica Full time ₹ 80,00,000 - ₹ 1,00,00,000
Key Informatica Development Role

The successful candidate will be responsible for delivering ETL development, support, data cleansing, quality control, and transformation activities across multiple business applications.

This role requires handling day-to-day operations, troubleshooting, and participating in upgrades and process improvements.

  • Develop, enhance, and maintain Informatica mappings, workflows, and sessions.
  • Perform data extraction, transformation, and loading (ETL) from diverse sources such as flat files, Oracle DB, Salesforce, SAP, and others.
  • Execute file validation scripts, encryption/decryption, file creation, and secure transfers.
  • Support month-end activities, ensuring timely data loads and reconciliations.
  • Monitor and troubleshoot ETL job failures, system performance, and process bottlenecks.
  • Collaborate with cross-functional teams to support inflight projects.
  • Provide operational support for daily feeds across multiple geographies.
  • Participate in Informatica upgrade projects, service restarts, and automation initiatives.
  • Handle support tickets, ensuring SLA compliance and timely resolution.
  • Contribute to process improvement, documentation, and automation of recurring tasks.
Required Skills and Qualifications
  • 3–7 years of experience in Informatica PowerCenter / IICS.
  • Strong expertise in ETL design, development, and performance tuning.
  • Hands-on experience integrating with SAP, Salesforce, Oracle, and file-based systems.
  • Familiarity with file encryption/decryption tools and secure data transfer protocols.
  • Experience handling large-scale data.
  • Strong troubleshooting skills for job failures, connection issues, and performance bottlenecks.
  • Exposure to automation of validation processes, service restarts, and operational scripts.
  • Experience working in multi-shift support models and global team environments.
  • Good understanding of data quality, cleansing, and transformation best practices.

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