Sr. Data Engineer (GCP/Vertex AI)

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.