Gcp Vertex Ai Engineer Jobs

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Sr. Data Engineer (GCP/Vertex AI)

HEB San Antonio, TX

San Antonio, TX

Today

Full time Senior Artificial Intelligence Big Data

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Job Description

At H-E-B Digital Technology, this Sr. Data Engineer role supports data and machine learning infrastructure that powers personalized search and product recommendations. You will work alongside cross-functional teams to deliver scalable, production-grade solutions using Google Cloud Platform and Vertex AI for a customer experience platform serving millions of shoppers.

This position is based in San Antonio, TX and is an onsite role with a minimum of 5+ years of related data engineering experience.

What You’ll Do

Build and maintain data and machine learning infrastructure supporting the Customer Experience Engineering organization.
Own data orchestration, feature engineering, and model serving required for personalized search and product recommendations delivered to customers every week.
Collaborate with Data Science, Machine Learning Engineering, Search Engineering, Product Management, and Customer Experience teams to translate business goals into scalable, production-grade technical solutions.
Apply hands-on experience building and supporting personalized online product search, search ranking algorithms, semantic search, and large-scale product recommendation or customer personalization platforms.
Leverage GCP, including Vertex AI, Feature Stores, and MLOps practices to operationalize machine learning and personalization models in partnership with data and ML teams.
Use Python, PySpark, and SQL to develop and maintain large-scale data pipelines and perform large-scale data manipulation.
Apply expertise in modern data lake and Lakehouse architectures, data modeling, ETL/ELT pipelines, and real-time event-driven streaming using Kafka.
Design and build scalable APIs and low-latency data services that support machine learning applications in production.
Partner across Product, Data Science, and Engineering teams to deliver resilient technical solutions aligned to business objectives.

Required Qualifications

Advanced knowledge of Lean Startup / Agile methods.
Knowledge of business intelligence, analytics, reporting, and application integration.
Knowledge of data architectures such as data warehouse, data lake, and data mesh, including when to apply them.
Strong working understanding of data architecture and data modeling best practices across data and analytics platforms.
Strong working understanding of coding standards and design principles or patterns.
Strong prioritization skills.
Strong verbal and written communication and data presentation skills.
Ability to deliver on ambiguous projects with incomplete information.
Ability or willingness to learn new technologies as they emerge.
Ability to remain calm and effective under pressure.
Ability to work a flexible schedule as needed.
Ability to collaborate across multiple work locations.
Ability to work in a team environment and willingness to take feedback from peers and mentors.
A related degree or comparable formal training, certification, or work experience.
5+ years of experience related to data engineering.
Experience in Lean Startup or Agile development methodologies.
Experience working in large-scale infrastructure, large data sets, and mission-critical SLAs.

Technologies

Google Cloud Platform (GCP)
Vertex AI
Feature Stores
MLOps
Python
PySpark
SQL
Kafka

Nice-to-Have Qualifications

Previous background in retail, e-commerce, or high-volume digital commerce environments.
Familiarity with vector search, search indexing and relevance tuning, and recommendation methodologies such as collaborative filtering, content-based filtering, embeddings, and feature engineering.
Experience processing high-volume clickstream and behavioral event data, including work with Customer 360 platforms and customer identity resolution.
Knowledge of A/B testing, experimentation frameworks, and the metrics used to measure business impact of search and personalization models.

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