Responsibilities

As a Staff Data Engineer, you'll use an advanced analytical, data-driven approach to drive a deep understanding of our fast-changing business and answer real world questions. You'll work with stakeholders to develop a clear understanding of data and data infrastructure needs, resolve complex data-related technical issues, and ensure optimal data design and efficiency.

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 high-velocity contributions in multiple technical domains?

We are looking for:
- 8+ years of experience related to data engineering

What is the work?
• Designs data patterns that support creation of datasets for analytics; implements calculations, cleanses data, ensures standardization of data, maps / links data from more than one source
• Performs data validation and quality assurance on work of senior peers and write automated tests
• Maintains / streamlines / orchestrates existing data pipelines end to end
• Builds / supports complex data warehousing pipelines into cloud platforms GCP/AWS, data integrations, data streaming solutions, predictive model implementations with prompt engineering for AI Models, building out data quality checks into data pipelines that are on BigQuery or Databricks
• Works with peer staff engineers to perform design reviews and swiftly change patterns according to latest tools and technologies
• Designs and develops real-time streaming requirements by using structured streaming from either pub-sub or another streaming table on datalake
• Builds / supports more complex data pipelines including application programming interfaces (APIs)
• Identifies complex data from upstream sources to enable new capabilities.
• Engages in testing of the technical solutions to ensure data integrity and system functionality of own work and broader system, E2E
• Builds large-scale batch and real-time data pipelines with big data CDC processing frameworks
• Designs / develops data integrations to support application engineering and system integration
• Designs / develops / maintains large data pipelines; diagnoses / solves production support issues
• Creates documentation and training related to technology stacks and standards within assigned team
• Designs / implements monitoring capabilities based on business SLA and data quality
• Uses / contributes to refinement of Digital Engineering-related tools, standards, and training
• Engages / collaborates with external technical teams to ensure timely, high-quality solutions
• Engages with shared services teams and vendors when necessary
• Works closely with Product, Data Science, Application, and Analytics teams to develop a clear understanding of data and data infrastructure needs; assists with data-related technical issues; ensures optimal data design and efficiency
• Performs full SDLC process, including planning, design, development, certification, implementation, and support
• Interacts with Product, Business, Analyst stakeholders to confirm data quality, discuss requirements, and support data testing
• Peer reviews with team members; learns / adapts from peer review of own code
• Contributes to overall design, architecture, security, scalability, reliability, and performance
• Mentors / provides support to Senior Data Engineers
• Builds more complex data models to deliver insightful analytics; ensures highest standard in data integrity
• Has knowledge in machine learning concepts

What is your background?
• A related degree or work experience, preferably a Bachelors degree in related work stream
• 8+ years of experience related to data engineering
• Experience in Lean Startup or Agile development methodologies
• Experience working in large scale cloud infrastructure, large data sets, and mission critical SLAs
• Experience in Advanced SQL / Python.
• Have a data engineering certification from any of the cloud technologies

Do you have what it takes to be an H-E-B Staff Data Engineer?
• Advanced knowledge of Lean Startup / Agile methods
• Strong understanding 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 modeling 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 teams at multiple work locations
• Ability to work within a team, and willingness to take feedback from peers and mentors

Can you...
• Function in a fast-paced environment with the ability to work from home and / or office
• Work extended hours; sit for extended periods

JDENGINEERING

Last revised: 11/01/2024