Education: Bachelor's Degree or relevant experience.
Preferred Certification(s): Any relevant IT Certification (e.g., AWS Cloud Practitioner, Google Cloud Digital Leader, Azure Fundamentals, Databricks Lakehouse Fundamentals).
Experience: Less than one year of relevant or practical experience.
Full description
Management Level:
84
Work Shift:
1ST SHIFT (United States of America)The IT Data Engineer I builds foundational skills in SQL, Python, and data pipeline development. Working under direct supervision, this role supports data ingestion, transformation, and quality processes while developing awareness of cloud platforms, data governance, and AI-assisted development tools.
Essential Duties and Responsibilities
Delivers low-complexity data engineering tasks as part of a team. Works under direct supervision; receives instructions, guidance, and direction from others. Scope: Team.
Develop and maintain SQL-based data pipelines, ensuring efficient ETL processes.
Write Python scripts to support data transformation, ingestion, and automation tasks.
Develop foundational skills in working with common data serialization and interchange formats (e.g., JSON, CSV, Parquet, Avro) for data ingestion and transformation.
Learn and apply foundational concepts of data warehousing, data architecture, and basic data modeling (e.g., fact/dimension tables, normalization).
Assist in applying data classification standards to datasets and pipelines under guidance, learning to identify data sensitivity levels (e.g., public, internal, confidential, restricted).
Provide assistance in data governance, data quality, and data privacy activities, including following PII handling protocols and data retention policies. Escalate potential data exposure or classification issues to senior engineers.
Use version control systems (e.g., Git) for all code and configuration changes, including branching, committing, and participating in pull requests.
Gain foundational exposure to major cloud platforms (e.g., AWS, GCP, or Azure) and understand how data services operate in a cloud environment.
Develop basic awareness of containerization concepts and how pipelines are packaged and deployed.
Learn basic data testing and validation practices using data quality frameworks to ensure pipeline output quality.
Assist in implementing basic logging and monitoring for data pipelines to support troubleshooting and operational visibility.
Collaborate with team members and stakeholders to understand requirements for data solutions.
AI-Assisted Engineering
Develop a foundational understanding of AI/ML concepts and their application to data pipelines and automation.
Learn to use AI-assisted tools and copilots to accelerate data engineering tasks such as code generation, debugging, and documentation.
Gain exposure to prompt engineering fundamentals and how large language models (LLMs) can support data operations.
Understand that AI-generated outputs can be inaccurate; learn to validate and verify AI-produced code, queries, and results before use.
Qualifications
Education: Bachelor's Degree or relevant experience.
Preferred Certification(s): Any relevant IT Certification (e.g., AWS Cloud Practitioner, Google Cloud Digital Leader, Azure Fundamentals, Databricks Lakehouse Fundamentals).
Experience: Less than one year of relevant or practical experience.
Special Skills
Proficiency in SQL and foundational Python scripting.
Understanding of data warehousing concepts, basic data modeling, and basic data architecture.
Familiarity with common data serialization and interchange formats.
Foundational exposure to modern cloud data platforms and at least one major cloud platform (e.g., AWS, GCP, or Azure).
Basic proficiency with version control systems for collaborative development.
Basic awareness of AI/ML concepts and AI-assisted development tools for code generation and data analysis.
Soft Skills
Curiosity: Eagerness to explore and understand new data concepts, AI technologies, and emerging patterns.
Receptiveness to Feedback: Willingness to accept and act on coaching from senior engineers.
Attention to Detail: Meticulous approach to data handling and analysis.
Collaboration: Ability to work effectively in cross-functional teams.
Communication: Clear and concise communication of technical concepts.
Reliability: Consistently meeting deadlines and following through on commitments.
Adaptability: Willingness to learn new technologies, including AI-driven tools, and adapt to change.
* Not eligible for immigration/work authorization support now or in the future Not eligible for relocation assista**nce *
Internal Management & Management Support Applicants:
Automatic notification to your current manager will be initiated upon selection for interview. This applies to all candidates who are level 79 or above.
All professional team members are expected to demonstrate responsible use of approved AI tools, including safeguarding sensitive information, adhering to company policies, and validating AI-generated outputs. Individual Contributors should demonstrate the ability to integrate AI into daily work, improve efficiency through AI-enabled solutions, evaluate outputs critically, and apply professional judgment when using AI. People Leaders should demonstrate the ability to drive responsible AI adoption, enable effective use of approved solutions, identify opportunities to improve team performance through AI, and ensure accountability for the quality and accuracy of AI-supported outcomes.
Relocation Assistance Eligible:
No
Referral Payout Eligible:
Yes For Professional Management levels, internal applicants should either upload a resume to their application OR complete their application fully showing current and past work experience in the sections provided.
The successful candidate(s) must be willing and able to perform the physical requirements of the job with or without a reasonable accommodation.
We provide our team members and their families with paid time off; 401(k) plans; affordable health, life, dental, vision and prescription drug benefits; and more.
Tyson is an Equal Opportunity Employer. All qualified applicants will be considered without regard to race, national origin, color, religion, age, genetics, sex, sexual orientation, gender identity, disability or veteran status.
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