Data Transformation & Automation Engineer

Data Transformation & Automation EngineerPosition Summary
As a GSC Data Transformation & Automation Engineer, you will play a critical role in enabling data-driven decision making across Global Supply Chain operations by designing, developing, and maintaining scalable data solutions.

You will be responsible for the end-to-end lifecycle of data, including data ingestion, ETL processes, transformation, automation, quality management, and delivery of trusted datasets for analytics and reporting.

In this role, you will partner with global and regional stakeholders to drive transformation initiatives involving data migration, harmonization, master data governance, and process standardization.

You will leverage SQL, Python, ETL frameworks, automation technologies, and business intelligence tools to build sustainable solutions that improve data reliability, operational efficiency, and business performance.

As a subject matter expert in data engineering and automation, you will independently solve complex technical challenges, optimize existing data models and pipelines, and contribute to strategic digital transformation initiatives across the organization.
Key Responsibilities


* Design, develop, maintain, and optimize ETL/ELT pipelines to support data integration, transformation, and delivery across multiple business systems.


* Build and manage scalable data ingestion processes that ensure reliable and timely availability of data for operational and analytical use cases.


* Develop complex SQL queries, stored procedures, views, and data models to support reporting, analytics, and business intelligence requirements.


* Participate in global and regional transformation projects involving data migration, data harmonization, master data alignment, and process standardization.


* Collaborate with cross-functional and cross-cultural teams to align business requirements with data and automation solutions.


* Transform, cleanse, and standardize raw data from multiple sources into consistent, business-ready datasets.


* Implement data validation frameworks and quality controls to ensure data accuracy, completeness, consistency, and integrity.


* Monitor data pipelines and platform performance, identifying and resolving data integration, transformation, and migration issues.


* Develop proactive monitoring, alerting, and troubleshooting capabilities to improve system reliability and reduce operational support efforts.


* Identify and implement automation opportunities that eliminate manual activities and improve process efficiency across supply chain operations.


* Support the design and implementation of testing frameworks for data extraction, transformation, and loading processes.


* Lead root-cause analysis, bug fixes, data model enhancements, and performance optimization initiatives.


* Deliver trusted datasets and scalable data structures that support dashboards, reports, advanced analytics, and busi...