Senior Data Engineer, Customer & Identity Resolution

HEB is building data capabilities that power analytics and improve customer and identity resolution. In this Senior Data Engineer role, you will design and deliver the patterns, pipelines, integrations, and APIs that keep data reliable, validated, and usable across teams. The position is based onsite in Austin, TX 78702 and includes end-to-end ownership, from planning through support.

What you’ll do

• Design data patterns that enable analytics dataset creation, including calculations, data cleansing, standardization, and mapping or linking data across multiple sources.
• Run data validation and quality assurance on work produced by junior peers, and develop automated tests to support correctness.
• Maintain and streamline existing data pipelines end to end.
• Build and support advanced pipelines, application programming interfaces (APIs), data integrations, data streaming solutions, and predictive model implementations focused on quality and velocity.
• Identify complex upstream data opportunities that unlock new capabilities.
• Test technical solutions to confirm data integrity and system functionality for your work and broader end-to-end systems.
• Develop large-scale batch and real-time pipelines using big data processing frameworks.
• Design, develop, and maintain large data pipelines while diagnosing and resolving production support issues.
• Create documentation and training for team technology stacks, standards, and related practices.
• Design and implement monitoring aligned to business SLAs and data quality expectations.
• Contribute to refinement of Digital Engineering tools, standards, and training.
• Collaborate with external technical teams and coordinate with shared services teams and vendors when needed to deliver timely, high-quality solutions.
• Work closely with Product, Data Science, Application, and Analytics teams to clarify data and data infrastructure needs, assist with data-related technical issues, and improve data design and efficiency.
• Support the full SDLC, including planning, design, development, certification, implementation, and ongoing support.
• Participate in discussions with Product, Business, and Analyst stakeholders to confirm data quality, align on requirements, and support data testing.
• Perform peer code reviews, applying feedback and iterating based on review outcomes.
• Contribute to architecture, security, scalability, reliability, and performance for the overall platform.
• Mentor and support junior Data Engineers.
• Build more complex data models to deliver analytics insights while maintaining high standards for data integrity.
• Apply knowledge of machine learning concepts as part of relevant initiatives.

Experience and qualifications

• 5+ years of experience related to data engineering.
• A related degree or comparable formal training, certification, or work experience.
• Experience using Lean Startup or Agile development methodologies, with advanced knowledge of Lean Startup or Agile methods.
• Experience in large-scale infrastructure, large data sets, and mission-critical SLAs.
• High proficiency in Python, PySpark, and SQL for large-scale data manipulation and pipeline development.
• Proven experience with Google Cloud Platform (GCP) and managed services, including Cloud Dataproc (Spark), Cloud Dataflow, Apache Airflow (Cloud Composer), Google Cloud Storage, and Cloud Pub/Sub.
• Knowledge of modern data lakehouse architectures such as Databricks and BigQuery, plus scalable ETL/ELT pipelines.
• Knowledge of business intelligence, analytics and reporting, and application integration.
• Strong understanding of data architecture and data modeling best practices across data and analytics platforms.
• Demonstrated experience building and deploying internal data-serving REST APIs using frameworks like FastAPI, including integration with downstream applications and microservices.
• Strong adherence to software engineering best practices such as unit testing, integration testing, code reviews, Git branching strategies, and CI/CD automation.
• Ability to prioritize, communicate clearly in verbal and written formats, and present data effectively.
• Willingness and ability to learn new technologies as they emerge.
• Ability to work calmly under pressure and collaborate across multiple work locations.
• Ability to work within a team, accept feedback from peers and mentors, and support a flexible schedule as needed.

Technologies

• Python, PySpark, SQL
• Google Cloud Platform (GCP), Cloud Dataproc (Spark), Cloud Dataflow
• Apache Airflow (Cloud Composer), Google Cloud Storage, Cloud Pub/Sub
• Databricks, BigQuery
• FastAPI, REST APIs
• ETL/ELT
• Machine learning concepts
• CI/CD, Git

Nice-to-have

• Retail concepts, including prior experience with POS/transactions and customer or identity resolution.
• Working knowledge of Neo4j and the Cypher / ISO GQL query language.

Additional details

• Ability to function in a fast-paced environment and work from the office.
• Ability to work extended hours and sit for extended periods.
• Onsite location: Austin, TX 78702.