Join our expanding team as a Data Migration Engineer, a pivotal role in transforming complex data workflows. This position focuses on leveraging modern data engineering tools to replicate and enhance existing Informatica processes within a Python and dbt environment. You will be instrumental in building robust data pipelines and ensuring data integrity throughout the migration.

This opportunity is ideal for engineers passionate about data architecture and optimization, contributing directly to the efficiency and scalability of our data systems. You'll work with high-volume datasets and cutting-edge technologies to drive successful data initiatives.

Key responsibilities include assessing intricate Informatica workflows and translating them into equivalent Python EL scripts and dbt transformation models. You will develop and maintain high-volume data pipelines, design dbt transformation models adhering to best practices, and implement comprehensive testing strategies.

Orchestrate Python EL and dbt scripts using Airflow, contributing to GitLab CI/CD pipelines for code quality and deployment. Peer code reviews, performance troubleshooting, and technical documentation are also vital aspects of this role.

We are seeking a skilled engineer proficient in translating Informatica workflows into Python EL scripts and dbt transformation models. Experience with high-volume data pipelines and tools like SQLAlchemy, cx_Oracle, pyodbc, Oracle Data Pump, and SQL Server BCP is essential.

Familiarity with dbt best practices, native testing, and Python unit tests is required. Experience in developing Airflow DAGs and contributing to GitLab CI/CD pipelines is also a key requirement. Strong troubleshooting skills for performance and data discrepancies are necessary.