Jobs · Information Technology · Texas

Senior Data Engineer (Austin, or Dallas)

H-E-B · Austin, TX · 2 mo ago
On-siteInformation TechnologyFull-time

About the role

As a Senior 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.

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 junior peers and write automated tests
  • Maintains / streamlines existing data pipelines end to end
  • Builds / supports more complex data pipelines, application programming interfaces (APIs), data integrations, data streaming solutions, predictive model implementations (quality, velocity, etc.)
  • Identifies more 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 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 other team members code; learns / adapts from peer review of own code
  • Contributes to overall design, architecture, security, scalability, reliability, and performance
  • Mentors / provides support to junior Data Engineers
  • Builds more complex data models to deliver insightful analytics; ensures highest standard in data integrity

Qualifications

  • Related degree or comparable formal training, certification, or work experience
  • Advanced knowledge of Lean Startup / Agile methods
  • Knowledge of 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 modelling 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 work locations
  • Ability to work within a team, and willingness to take feedback from peers and mentors

Work Experience

Experience related to data engineering, including experience in Lean Startup / Agile development methodologies, large scale infrastructure, large data sets, and mission critical SLAs.

Working Conditions

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

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