Sr Data Engineer- Informatica

3 days ago


Tempe, Arizona, United States Irvine Technology Corporation Full time

About the Role

We're looking for a hands-on Informatica Cloud Data Engineer to design, build, and optimize enterprise-scale data pipelines that connect Master Data Management (MDM) systems with modern cloud data environments like Snowflake and Databricks. This role is ideal for someone who enjoys working across multiple data platforms, improving data quality, and bringing structure to complex data ecosystems.

What You'll Do

  • Key Responsibilities
    Design, build, and maintain robust ETL/ELT data pipelines that integrate MDM systems with Snowflake and Databricks.
  • Configure and optimize Informatica Cloud environments for scalability, data throughput, and operational efficiency.
  • Implement data quality and governance frameworks to ensure data integrity, lineage, and compliance with internal standards.
  • Collaborate with data architects, business analysts, and engineering teams to define integration requirements and streamline data delivery across platforms.
  • Support and lead the migration of legacy VBX systems into a modern, cloud-native Informatica environment.
  • Automate data ingestion, transformation, and validation processes using best practices in workflow orchestration.
  • Troubleshoot data integration issues, perform root-cause analysis, and ensure reliable job execution and monitoring.
  • Contribute to data architecture documentation, reusable templates, and process improvements to accelerate delivery.

  • Qualifications
    7+ years of experience in data integration, ETL development, or data engineering, ideally within a cloud environment.

  • Deep hands-on expertise with Informatica Cloud (IICS) — including mappings, tasks, and workflow orchestration.
  • Proven ability to build and manage data pipelines connecting to Snowflake, Databricks, and other modern data platforms.
  • Solid understanding of Master Data Management (MDM) concepts, data governance principles, and data quality management.
  • Proficiency in SQL and comfort working with large-scale, structured and semi-structured data.
  • Familiarity with API integrations, REST/SOAP, or real-time data movement a plus.
  • Strong problem-solving mindset with the ability to diagnose and resolve complex data issues end-to-end.

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