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Tier-1 brand, metro location, mid-level experience and common data-engineer title increase competition.
Core data engineering skills transfer well, but Informatica-to-modern-stack migration specialization reduces portability somewhat.
Multiple explicit years and mandatory Informatica/dbt/Airflow/Python/SQL requirements enforce strict filtering.
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Design and implement Python extract/load pipelines, dbt transformations, and Airflow orchestrations to migrate from Informatica PowerCenter to a modern data stack.
Translate complex Informatica workflows (sessions, mappings, parameterizations) into Python EL scripts, dbt models, and Airflow DAGs that are production-quality and functionally equivalent at enterprise scale.
Troubleshoot data discrepancies, manage high-volume data movement, contribute to CI/CD pipelines, code reviews, and technical documentation.
5+ years of hands-on Informatica PowerCenter experience including mappings, sessions, workflows, and parameterizations.
3+ years hands-on experience in dbt Core with model layering, macros, tests, and incremental materialization.
3+ years of Airflow experience including DAG authoring and task dependencies.
5+ years of Python experience with production use of parallelism and batch data processing; 5+ years of SQL experience involving complex queries; experience with Oracle Data Pump or SQL Server BCP for bulk data movement.
Experienced in converting Informatica workflows to modern data engineering tools (Python, dbt, Airflow) at scale with production-quality results.
Strong technical contributor capable of troubleshooting, peer code reviewing, and improving CI/CD pipelines.
Comfortable working on high-volume data pipelines and complex SQL-based data transformations in enterprise environments, possibly mentoring junior engineers.