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Open nowPosted 78 days ago

Staff Data Engineer-AI Platform

H-E-B1,209 open roles

Where
Austin, Texas, United States
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Your applicationOpen nowStaff Data Engineer-AI PlatformH-E-B · Austin, Texas, United States

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. H-E-B postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 78 days ago

H-E-B median: 1 days open

The posting

Responsibilities Job Summary: As a Staff Data Engineer, you'll lead, coach, and mentor engineers and teams and provide technical direction and support. You'll collaborate with Product, Data Science, Application, and Analytics teams to develop a clear understanding of data and data infrastructure needs to resolve data-related technical issues and ensure optimal data design and efficiency. Key Responsibilities & Essential Functions: Design & Development: Leads team in designing / developing data integrations that support application engineering and system integration Leads design / development / maintenance of largescale data pipelines; may assist in diagnosing / solving complex production support issues Provides operational and technical expertise to design algorithms patterns that support large/complex datasets for analytics, implement calculations, cleanse data, ensure standardization of data, and map / link data from more than one source Leads engineers across one or more squads to deliver initiatives Mentors / provides support to junior data engineers; coaches / mentors engineers in engineering techniques, processes, new technologies Builds / supports complex data pipelines, APIs, data integrations, data streaming solutions, and predictive model implementations Identifies complex data from upstream sources to enable new capabilities Designs and builds large-scale batch / real-time data pipelines with big data processing frameworks Architects monitoring capabilities based on business SLA and data quality Maintains / streamlines existing data pipelines end to end Performs full SDLC process, including planning, design, development, certification, implementation, and support on more complex projects Establishes team operational plans; develops / implements new processes, standards, and operational plans that impact results; develops technical roadmaps Makes recommendations for overall data platforms, work flow, design, architecture, security, scalability, reliability, and performance Recommends changes to processes, tools at the group / dept level based on industry standards, patterns, and practices Tests technical solutions to ensure data integrity and system functionality of own work, with consideration toward broader system, E2E Designs scalable, efficient data models to support data integration, storage, and retrieval across complex systems. Develops and implements data quality framework for data accuracy, consistency, and completeness across workflows. Works with Product, Business, and Analyst stakeholders to confirm data quality, discuss requirements, and support data testing Creates team documentation and training related to technology stacks and standards Diagnoses / troubleshoots extremely complex issues independently Performs data validation and quality assurance on own work and of junior engineers Collaborates with external technical teams to ensure timely, high-quality solutions Engages with shared services teams and vendors as needed Influences others in technical decision-making / technology adoption in assigned domain Knowledge in machine learning concepts The responsibilities and essential functions outlined above describe the general nature and level of work assigned to this position. This is not an exhaustive list of all duties, responsibilities, and skills required. Duties and responsibilities may be modified at any time based on business needs. Employees may be required to perform other job-related tasks as requested by their supervisor, subject to reasonable accommodations. Qualifications & Key Requirements: Work Experience: of experience related to data engineering - leadership experience - Experience in team leadership - Experience working in large scale infrastructure - large data sets - and mission critical SLAs - Knowledge/Skills/Abilities: Comprehensive knowledge of Lean Startup / Agile development methodologies - Knowledge of business intelligence, analytics / reporting, and application integration - Knowledge of data architectures such as data warehouse, data lake, and data mesh and when to apply - Expert understanding of coding standards, design principles / patterns, and data architecture and data modeling best practices and guidelines for different data and analytic platforms - Advanced verbal / written communication and data presentation skills - Strong prioritization skills - Ability to deliver on ambiguous projects with incomplete information - Ability to act as a thought leader and mentor to junior team members - 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 - Education: A related degree or comparable formal training, certification, or work experience - Licenses/Certifications: Physical Demands & Working Conditions: Function in a fast-paced environment Work extended hours; sit for extended periods The work environment characteristics described here are representative of those a Partner encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Last revised: 11/01/2024 JDENGINEERING

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