Staff Data Engineer-GCP/Data Solutions (San Antonio, Austin or Dallas)

HEB•Dallas, TX

About The Position

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. 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. 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?

Requirements

8+ years of experience related to data engineering
A related degree or work experience, preferably a Bachelors degree in related work stream
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
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
Function in a fast-paced environment with the ability to work from home and / or office
Work extended hours; sit for extended periods

Responsibilities

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