Sr Data Engineer - GCP

We are looking for a Data Engineer to join our client team. In this role, you'll design, build, and tune scalable data pipelines using PySpark within the Google Cloud Platform (GCP) ecosystem. Youll be responsible for both creating new pipelines and improving existing ones, playing a critical role in transforming and delivering high-quality data that powers key business decisions.

The final client operates in the retail sector, using advanced analytics and AI to enhance customer experiences and operational efficiency. This role supports their Vertex AI-powered ML workflows and real-time analytics using BigQuery and Dataform.

This project focuses on large-scale data processing, building cloud-native pipelines, and supporting ML workflows through GCP technologies.

Location: Must reside and have work authorization in Latin America.

Availability: Must be available to work with significant overlap with Central Time.

The Ideal Candidate Has

• 4-6 years of experience in a data engineering or similar role.
• Extensive hands-on experience with Google Cloud Platform (GCP), especially BigQuery, Vertex AI, and Dataform.
• Deep experience writing and tuning Spark jobs using PySpark.
• Proven ability to build and maintain scalable, cloud-native data pipelines.
• Understanding of how to support machine learning workflows via data pipelines.
• Strong SQL skills and familiarity with BigQuery analytics (25% of the workload).
• Excellent collaboration skills, with experience working with both technical teams and stakeholders.
• Excellent communication skills in English (C1 preferred, strong B2 may be considered).

Nice To Have

• Experience with Scala and the Akka toolkit.
• Familiarity with React (purely optional, no frontend work expected).
• Previous experience in the retail industry is a plus, but not required.

Key Responsibilities

• Design, implement, and optimize cloud-native data pipelines using PySpark and GCP services.
• Collaborate with technical teams and stakeholders to understand data requirements and deliver reliable solutions.
• Write efficient, production-ready Spark jobs and ensure they are properly tuned for performance.
• Support and improve existing pipelines while contributing to new development efforts.
• Leverage BigQuery for analytical processing and Vertex AI for supporting ML-related pipelines.
• Maintain high-quality code, participate in code reviews, and contribute to the technical roadmap.
• Work within a collaborative team environment, replacing a previous engineer and supporting the teams daily workflows.

Perks

• Work from home position.
• USD payment.
• Private Medical Insurance.
• Corporate Access to Udemy Corporate Udemy Account.
• 3 Sick Days per year.
• Birthday Off.
• Extra Days for Special Occasions.