Lead Data Engineer / Data Migration Engineer Informatica to dbt/Snowflake @ Chicago, IL

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Data Engineering
Data Migration
Business Rules
Core Data
Data Processing
ELT
ETL Architecture
Extract
Transform
Load
Migration
Management
Macros
Snow Flake Schema
Warehouse
Workflow
Informatica PowerCenter
Testing
SQL
Informatica

Job Details

Hello,

Hope you are doing well,

Role: Lead Data Migration Engineer: Informatica to dbt/Snowflake

Location: Chicago, IL - 3 to 4 days onsite

Duration: 12 Months +

Rate: Open

Role Summary

We are hiring a Lead Data Migration Engineer to drive the modernization of our core data warehouse. This critical, client-facing role involves the complete end-to-end migration of legacy ETL infrastructure from Informatica PowerCenter/Cloud to a cutting-edge ELT framework built on dbt and Snowflake. You will leverage deep expertise in both legacy ETL architecture and the modern cloud data stack to ensure a seamless, high-quality, and performant transition.

Key Accountabilities

Data Platform Modernization Leadership

  • Serve as the technical lead for reverse-engineering and comprehensively documenting complex ETL workflows, mappings, and business rules within Informatica PowerCenter/Cloud.
  • Architect, develop, and govern the new data transformation layer using dbt (Core/Cloud), emphasizing modularity, reusability (macros, packages), and rigorous adherence to analytics engineering best practices.
  • Develop highly optimized, production-grade SQL against Snowflake, focusing on cost efficiency, performance tuning, and scalable ELT data processing.

Qualifications and Experience

Required Technical Expertise

  • 10+ Years of Data Engineering Experience with a minimum of 2+ years focusing on cloud data migrations.
  • Expert Proficiency in Informatica: Proven, recent, hands-on development experience with Informatica PowerCenter or Informatica Cloud (IICS) mappings, workflows, and administration.
  • Mastery of dbt: Deep, practical experience building and deploying production-level data transformation pipelines using dbt, including advanced features like custom macros, package management, and testing frameworks.
  • Advanced knowledge of Snowflake architecture, including advanced SQL, query performance optimization, and experience with modern data ingestion methods (Snowpipe, COPY INTO).
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