ResponsibilitiesOur Data Engineering team builds and maintains the data and machine learning infrastructure that supports H-E-B’s Customer Experience Engineering organization. We own the data orchestration, feature engineering, and model serving required to deliver personalized search and product recommendations to millions of H-E-B customers every week.
As a Sr. Data Engineer, you will work cross-functionally with Data Science, Machine Learning Engineering, Search Engineering, Product Management, and Customer Experience teams to translate business objectives into scalable, production-grade technical solutions.
Once you’re eligible, you’ll become an Owner in the company, so we’re looking for commitment, hard work, and focus on quality and Customer service. “Partner owned” means our most important resources—People— drive the innovation, growth, and success that make H-E-B The Greatest Omnichannel Retailing Company.
Location:
San Antonio, Tx. (On-site)
Do you have a:
HEART FOR PEOPLE… you’re willing to facilitate solutions with multiple engineers, provide upward communication, and mentor others?
HEAD FOR BUSINESS… you consistently demonstrate and uphold the standards of coding, infrastructure, and process?
PASSION FOR RESULTS… you’re capable of you’re capable of high-velocity contributions in multiple technical domains?
What is the work?
- Search & Personalization Expertise: Hands-on experience building and supporting personalized online product search, search ranking algorithms, semantic search, and large-scale product recommendation or customer personalization platforms.
- Cloud & ML Infrastructure: Proven experience working with Google Cloud Platform (GCP), specifically leveraging Vertex AI, Feature Stores, and MLOps practices to operationalize machine learning and personalization models in partnership with Data Scientists and ML Engineers.
- Programming & Data Processing: Strong proficiency in Python, PySpark, and SQL for large-scale data manipulation and pipeline development.
- Data Architecture & Streaming: Deep understanding of modern data lake/Lakehouse architectures, data modeling, ETL/ELT pipelines, and real-time event-driven streaming using Kafka.
- Services & APIs: Experience designing and building scalable APIs and low-latency data services that power machine learning applications in production.
- Cross-Functional Collaboration: A track record of partnering across Product, Data Science, and Engineering teams to turn business objectives into resilient technical solutions.
Nice-to-Have Qualifications:
- Domain Experience: Previous background in retail, e-commerce, or high-volume digital commerce environments.
- Advanced ML & Search Techniques: Familiarity with vector search, search indexing/relevance tuning, and recommendation methodologies (e.g., collaborative filtering, content-based filtering, embeddings, and feature engineering).
- Behavioral & Customer Data: Experience processing high-volume clickstream and behavioral event data, as well as working with Customer 360 platforms and customer identity resolution.
- Experimentation & Measurement: Knowledge of A/B testing, experimentation frameworks, and metrics used to measure the business impact of search and personalization models.
Do you have what it takes to be an H-E-B Senior Data Engineer?
- Advanced knowledge of Lean Startup / Agile methods
- Knowledge of business intelligence, analytics and reporting, and application integration
- Knowledge of data architectures such as data warehouse, data lake, and data mesh and when to apply
- Strong working understanding of data architecture and data modelling best practices and guidelines for various data and analytic platforms
- Strong working understanding of coding standards and design principles / patterns
- Strong prioritization skills
- Strong verbal / written communication and data presentation skills
- Ability to deliver on ambiguous projects with incomplete information
- Ability / willingness to learn new technologies as they emerge
- Ability to calmly work under pressure
- Ability to work a flexible schedule as needed
- Ability to collaborate across multiple work locations
- Ability to work within a team, and willingness to take feedback from peers and mentors
What is your background?
- 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
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