Data Engineer, Worldwide Grocery Data & Analytics

Worldwide Grocery Store Tech (WWGST) is hiring a Data Engineer to join the Data & Analytics organization. This onsite role in Austin, TX focuses on building reliable data infrastructure and advanced pipelines that support generative AI, machine learning, BI, and retrieval-augmented generation (RAG) across grocery operations.

You will work with an AI-first cross-cutting data engineering team (DASH) that serves the broader WWGS organization by transforming raw data into analytical datasets and enabling access for data consumers across the grocery data community.

What you’ll do

• Build and maintain the infrastructure that enables data-driven decision making using software engineering best practices, data management fundamentals, data storage principles, and distributed systems.
• Manage and optimize cloud computing resources, with a focus on AWS, to support data infrastructure.
• Design, build, and maintain reliable, well-tested data pipelines with strong data quality practices including validation, deduplication, PII handling, and monitoring.
• Deliver performant transformations using SQL and Python, while applying rigorous data quality measures for training and retrieval datasets (including validation and drift detection).
• Use AI-assisted development tools (examples include Amazon Q and Kiro) to accelerate pipeline development, SQL work, and debugging, and validate AI-generated output for correctness.
• Partner with Business Intelligence Engineers on reporting, analysis, integrity, testing, validation, and documentation practices.
• Work with Data Scientists and analytics teams to make high-quality, well-governed data available at scale, supporting future machine learning use cases.
• Contribute to architecture and technology decisions that support a world-class user experience and align with business objectives.
• Develop in-depth knowledge of Amazon data sources to select appropriate resources for each use case, and iterate quickly through proofs of concept amid ambiguity.
• Create extensible, easy-to-maintain designs with a long-term vision.

Basic qualifications

• 2+ years of data engineering experience.
• Experience with data modeling, data warehousing, and building ETL pipelines.
• Experience writing and optimizing SQL queries with large-scale, complex datasets.
• Experience with one or more scripting languages (examples include Python and KornShell).
• Bachelor’s degree in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline.

Preferred qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR.
• Master’s degree in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline.
• Experience using AI-assisted development tools in academic or professional settings.
• Experience in RAG/LLM data integration.
• Experience with prompt engineering fundamentals.

Tools and technologies

SQL, Python, KornShell, AWS, Amazon Q, Kiro, Hadoop, Hive, Spark, EMR

Compensation and employment

Salary: USD 101,300 to 160,000 per year.

Location: Austin, TX (onsite).

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave