Data Engineer (ETL)

Data Engineer-ETL (Data Migration & Validation)

Role Overview

We are looking for an ETL Engineer with strong experience in data migration, validation,
and transformation to support the large-scale migration of legacy warehouse systems to Snowflake. The candidate will develop ingestion and transformation jobs, perform data reconciliations, and ensure data quality and completeness across multiple banking systems.

Key Responsibilities

Develop and execute ETL/ELT pipelines to migrate data from Fiserv, CardWorks, PCFS, HR, and Finance systems. Perform data profiling, validation, and reconciliation between source and Snowflake targets. Build ingestion frameworks (batch, incremental, CDC) using Azure Data Factory or Airflow. Support historical data loads and incremental refreshes. Implement data quality checks, audit logs, and error handling for ETL jobs. Collaborate with architects to align with Bronze–Silver–Gold data layer design. Optimize data loads and queries for performance and cost efficiency. Maintain pipeline documentation, mapping sheets, and validation scripts. Required Skills & Experience 4–8 years of hands-on ETL experience using SQL, Python, Spark, Azure Data Factory, or Informatica. Proven track record in data migration and validation projects to Snowflake or equivalent. Strong understanding of data quality frameworks, validation, and reconciliation techniques. Solid SQL debugging and performance optimization skills. Experience with CI/CD automation for data pipelines preferred. Strong analytical and teamwork skills.