What we’re looking for:

We are seeking an experienced Data Engineer to support the modernization of our enterprise data platform as we continue migrating from on‑premise systems to a cloud‑native architecture on Google Cloud Platform (GCP) . This is a hands‑on, individual contributor role focused on building scalable, reliable data pipelines that power analytics, reporting, and data products across the organization.

In this role, you’ll work across the full data lifecycle—from ingestion and transformation to governance and consumption—while partnering closely with supply chain, analytics, and global market teams. The work blends project‑based cloud migration with operational data ingestion support , offering both ownership and variety.

What your day-to-day may include:

• Designing, building, and maintaining ETL/ELT data pipelines using Python and SQL
• Migrating legacy on‑premise data warehouses and BI datasets to cloud platforms
• Supporting BI and data warehouse migration initiatives , including large-scale supply chain data
• Responding to and resolving data ingestion tickets from global markets
• Collaborating with analysts, data scientists, and business partners to understand data requirements
• Implementing data quality, monitoring, and reliability practices
• Leveraging modern developer tools, including AI‑assisted coding tools , to improve efficiency
• Contributing to governance activities such as metadata management, tagging, and lineage tracking

This role balances heads‑down engineering work with collaboration and cross‑functional problem solving.

• 1+ years of hands‑on experience as a Data Engineer or similar role
• Advanced proficiency in SQL , including query optimization and data modeling
• Strong programming experience in Python for data pipelines and automation
• Experience designing and building ETL/ELT pipelines for enterprise data platforms
• Hands‑on experience with at least one cloud platform (GCP preferred; AWS or Azure acceptable)
• Experience with distributed or big‑data processing frameworks (e.g., Spark, Beam, Hadoop )
Bachelor’s degree in Computer Science, Data Engineering, or a related technical field (or equivalent experience)

• Familiarity with Google Cloud Platform services such as BigQuery, Dataflow, or Dataplex.
• Experience with modern data warehousing concepts (partitioning, clustering, performance tuning).
• Exposure to orchestration tools (Airflow / Cloud Composer or similar).
• Understanding of streaming or event‑driven data architectures (Pub/Sub, Kafka)
• Knowledge of data governance practices including metadata, lineage, and quality checks.
• Experience working in Agile/Scrum environments.
• Strong communication skills and ability to collaborate with technical and non‑technical partners.
Comfort navigating ambiguity and learning complex enterprise data ecosystems quickly.

Amway does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need Amway immigration sponsorship (e.g., H-1B, STEM OPT, TN, etc.) now or in the future.

The Data Engineering team is leading the transformation of our global data platform , moving from fragmented, localized, on‑premise systems to a unified, cloud‑native ecosystem on Google Cloud Platform.

Our platform serves as a single source of truth for enterprise data, delivering governed, reliable, and high‑quality datasets that power:

• Operational and executive reporting
• Advanced analytics and data science initiatives
• Analytical products used across global markets

The team partners closely with center‑led functional groups (ABO, Customer, Product) and Market Analytics teams worldwide. You’ll join a collaborative group of experienced engineers working on high‑impact modernization efforts, with opportunities to influence platform standards, tooling, and best practices while continuing to grow your technical skills.