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AI ETL Modernization Engineer

Grayson Martins

Full-time · Job · Berlin

About the role

Legacy ETL pipelines are the technical debt nobody wants to touch. They're fragile, undocumented, and critical. Our platform uses AI to understand legacy pipeline logic — parsing stored procedures, mapping data flows, and generating modern equivalents in Airflow and dbt that do the same thing but are maintainable, testable, and fast. You'll build the migration engine: a code analysis layer that understands legacy ETL logic (think: 3,000-line SQL stored procedures with no comments), a transformation mapper that converts legacy patterns to modern equivalents, and the validation framework that proves the new pipeline produces identical results to the old one. Every enterprise has ETL debt. Some have pipelines written in the 1990s that nobody alive fully understands. Making those pipelines modern without breaking anything is one of the most valuable — and underappreciated — problems in data engineering.

Responsibilities

  • Build code analysis systems for understanding legacy ETL pipeline logic
  • Design transformation mappers converting legacy patterns to Airflow and dbt
  • Implement validation frameworks proving output equivalence after migration
  • Handle complex legacy SQL stored procedures and undocumented data flows
  • Create documentation for migrated pipelines and modernized architectures

Requirements

  • 3+ years in data engineering with ETL pipeline experience
  • Strong SQL skills including complex stored procedure comprehension
  • Airflow and Spark experience for modern pipeline development
  • Familiarity with Snowflake or cloud data warehouse migration
  • Patience and detective skills for understanding undocumented legacy systems

Benefits

  • Fully remote — European time zones
  • 30 days PTO
  • $2,000 learning budget
  • Solving a universal enterprise data problem

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

python sql airflow spark snowflake

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python sql airflow spark snowflake docker aws

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