{"id":3487422,"url":"https://alion.io/job/tyson-foods-data-engineer-i-onsite","title":"Data Engineer I (Onsite)","company":{"id":46492,"name":"Tyson Foods","domain":"tysonfoods.com","url":"https://alion.io/company/tysonfoods","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":97,"open_postings":112,"ghost_share":0.009,"stale_share":0.241,"repost_share":0.116,"time_to_fill_p50_days":12,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Springdale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":56000,"max_usd":120000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":376},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-28T00:00:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-30T11:08:39Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Job Details:\nThe 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.\nEssential Duties and Responsibilities\nDelivers low-complexity data engineering tasks as part of a team. Works under direct supervision; receives instructions, guidance, and direction from others. Scope: Team.\nDevelop and maintain SQL-based data pipelines, ensuring efficient ETL processes.\nWrite Python scripts to support data transformation, ingestion, and automation tasks.\nDevelop foundational skills in working with common data serialization and interchange formats (e.g., JSON, CSV, Parquet, Avro) for data ingestion and transformation.\nLearn and apply foundational concepts of data warehousing, data architecture, and basic data modeling (e.g., fact/dimension tables, normalization).\nAssist in applying data classification standards to datasets and pipelines under guidance, learning to identify data sensitivity levels (e.g., public, internal, confidential, restricted).\nProvide 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.\nUse version control systems (e.g., Git) for all code and configuration changes, including branching, committing, and participating in pull requests.\nGain foundational exposure to major cloud platforms (e.g., AWS, GCP, or Azure) and understand how data services operate in a cloud environment.\nDevelop basic awareness of containerization concepts and how pipelines are packaged and deployed.\nLearn basic data testing and validation practices using data quality frameworks to ensure pipeline output quality.\nAssist in implementing basic logging and monitoring for data pipelines to support troubleshooting and operational visibility.\nCollaborate with team members and stakeholders to understand requirements for data solutions.\nAI-Assisted Engineering\nDevelop a foundational understanding of AI/ML concepts and their application to data pipelines and automation.\nLearn to use AI-assisted tools and copilots to accelerate data engineering tasks such as code generation, debugging, and documentation.\nGain exposure to prompt engineering fundamentals and how large language models (LLMs) can support data operations.\nUnderstand that AI-generated outputs can be inaccurate; learn to validate and verify AI-produced code, queries, and results before use.\nQualifications\nEducation: Bachelor's Degree or relevant experience.\nPreferred Certification(s): Any relevant IT Certification (e.g., AWS Cloud Practitioner, Google Cloud Digital Leader, Azure Fundamentals, Databricks Lakehouse Fundamentals).\nExperience: Less than one year of relevant or practical experience.\nSpecial Skills\nProficiency in SQL and foundational Python scripting.\nUnderstanding of data warehousing concepts, basic data modeling, and basic data architecture.\nFamiliarity with common data serialization and interchange formats.\nFoundational exposure to modern cloud data platforms and at least one major cloud platform (e.g., AWS, GCP, or Azure).\nBasic proficiency with version control systems for collaborative development.\nBasic awareness of AI/ML concepts and AI-assisted development tools for code generation and data analysis.\nSoft Skills\nCuriosity: Eagerness to explore and understand new data concepts, AI technologies, and emerging patterns.\nReceptiveness to Feedback: Willingness to accept and act on coaching from senior engineers.\nAttention to Detail: Meticulous approach to data handling and analysis.\nCollaboration: Ability to work effectively in cross-functional teams.\nCommunication: Clear and concise communication of technical concepts.\nReliability: Consistently meeting deadlines and following through on commitments.\nAdaptability: Willingness to learn new technologies, including AI-driven tools, and adapt to change.\n\n* Not eligible for immigration/work authorization support now or in the future *\n* Not eligible for relocation assista nce *\nAll 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:\nNoWork Shift:\n1ST SHIFT (United States of America)Certain roles at Tyson require background checks. If you are offered a position that requires a background check you will be provided additional documentation to complete once an offer has been extended.\nHourly Applicants ONLY -You must complete the task after submitting your application to provide additional information to be considered for employment.\nThe successful candidate(s) must be willing and able to perform the physical requirements of the job with or without a reasonable accommodation.\nTyson 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.\nWe 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.\nIf you would like to learn more about your data privacy rights and how you may use that information, please read our Job Applicant Privacy Noticehere .\nUnsolicited Assistance: Tyson Foods and its subsidiaries do not accept unsolicited support from external recruitment vendors for open positions within the United States. Any resumes or candidate profiles submitted by recruitment vendors or headhunters to any employee or applicant tracking system at Tyson Foods or its subsidiaries, without a valid written request and search agreement approved by HR, will be considered the property of Tyson Foods. 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