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Lead IT Data Engineer

Tyson Foods Springdale, AR

Springdale, AR

Today

Full time Backend Developer Manager Analytics

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Job Description

Tyson Foods is hiring a Lead IT Data Engineer (onsite) to lead enterprise data solutions for the Beef & Pork Analytics team, with a focus on governed cloud pipelines and production-ready analytics.

Responsibilities

Lead the design and implementation of data engineering solutions for Beef & Pork Analytics, including Fresh Meats data lake, hub, analytics, semantic, and reporting-ready data layers.
Convert business requirements, report needs, KPIs, functional specifications, and validation criteria into scalable data models, pipelines, transformations, and analytics-ready datasets.
Develop, enhance, and support data products that enable Fresh Meats reporting use cases.
Build and orchestrate complex ETL/ELT pipelines using approved enterprise patterns, including automation, dependency management, monitoring, alerting, and production support.
Support source-system integrations into Data@Tyson/GCP, including replication, freshness monitoring, reconciliation, and exception handling for DB2, SAP, USDA, and other internal/external sources.
Design for reuse across analytics projects using shared dimensions, conformed business definitions, enterprise business terms, and scalable modeling practices.
Implement and validate data security requirements, including role-based access, row-level security, column-level security, ARS roles, and data classification dependencies and DSS/security review requirements when applicable.
Partner with Data Governance, Data Stewards, Product Owners, Data Modeling Coaches, business SMEs, and reporting teams to ensure assets are documented, classified, stewarded, and aligned to approved terminology.
Support Collibra workflows by ensuring tables, fields, lineage, classifications, and business terms are identified, reviewed, and maintained as part of delivery.
Lead data quality, reconciliation, and observability practices so issues are detected proactively and traced from source systems through GCP layers to reporting outputs.
Participate in and lead architecture and data model reviews, GitLab merge request readiness, release planning, production promotion, and change approval activities.
Provide operational support for Beef & Pork Analytics products, including incident triage, service requests, data lake freshness issues, access/security questions, pipeline failures, and production reporting impacts.
Coordinate with business and IT stakeholders during issue resolution by communicating impact, status, root cause, remediation steps, and validation results clearly and timely.
Mentor data engineers and analysts in SQL, GCP, dbt, orchestration, data modeling, testing, documentation, and enterprise governance expectations.
Manage technical relationships with internal platform teams, vendors, and third-party partners to deliver needed tools, integrations, and platform capabilities.
Perform other assigned duties aligned with organizational vision, mission, values, and scope of practice.

Requirements

Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, Analytics, or related field, or equivalent combination of education and relevant experience.
5+ years of relevant, practical experience in data engineering, cloud data platforms, enterprise analytics, data warehousing, business intelligence, or related delivery.
Strong SQL skills and experience building analytical datasets for enterprise reporting, dashboards, semantic models, and downstream analytics consumption.
Hands-on experience with cloud data platforms, preferably GCP and BigQuery (or comparable cloud technologies).
Experience designing and supporting multi-layer data architectures (lake, hub, curated, analytics, semantic, dimensional, star-schema, or medallion-style models).
Experience with ETL/ELT development, orchestration, pipeline monitoring, job dependencies, failure handling, and production support.
Experience working with source-system data, preferably including ERP, mainframe, DB2, SAP, and datasets tied to manufacturing, sales, finance, pricing, or commodity-related domains.
Understanding of data governance, metadata, business terminology, lineage, stewardship workflows, data classification, and controlled promotion into production.
Experience implementing or supporting data security controls, including role-based, row-level, and column-level access patterns.
Experience with Git-based development, merge requests, code review, deployment discipline, testing evidence, and change approval documentation.
Experience with Kimball data warehouse methodology in a medallion raw-cleansed-curated architecture.
Ability to lead technical design discussions, identify risks, challenge assumptions, and recommend scalable, supportable solutions.

Technologies

SQL, GCP, BigQuery, ETL, ELT, DB2, SAP, USDA
Data@Tyson, Power BI, Cloud Storage
Dataproc, Pub/Sub, Composer/Airflow, Dataflow
dbt, Python, PySpark, Spark, Terraform, CI/CD
AtScale, Fivetran, HVR, CDC, Collibra, GitLab

Benefits

Paid time off
401(k) plans
Affordable health, life, dental, vision, and prescription drug benefits

Preferred Certification(s)

Google Cloud data engineering, analytics, data governance, Power BI, or other relevant IT certifications

Preferred Technical Skills

Experience with GCP services such as BigQuery, Cloud Storage, Dataproc, Pub/Sub, Composer/Airflow, Dataflow, or related tools.
Experience with dbt, Python, PySpark, Spark, Terraform, CI/CD, or other modern data engineering technologies.
Experience with Power BI, AtScale, semantic layer design, Fabric capacity awareness, or enterprise reporting consumption patterns.
Experience with Fivetran, HVR, CDC, data replication, freshness checks, or source-to-cloud ingestion monitoring.
Experience supporting USDA and analytics tied to commodity pricing, sales realization, profitability, finance, supply chain, order/invoice, customer, product, or manufacturing.
Experience with data quality frameworks, automated reconciliation routines, observability tooling, or audit-ready validation practices.
Experience supporting AI, machine learning, automation, or advanced analytics use cases through trusted and well-modeled data assets.

Soft Skills

Technical Leadership: Senior technical contributor who leads complex engineering work and coaches others toward durable, governed solutions.
Business Partnership: Builds relationships with business SMEs, product managers, analysts, data stewards, and platform teams.
Execution Ownership: Drives work from discovery and design through development, validation, production deployment, support, and continuous improvement.
Communication: Explains data concepts, technical tradeoffs, risks, timelines, dependencies, and decisions to technical and non-technical stakeholders.
Detail Orientation: Values accuracy, traceability, and documentation for business-critical reporting, validation, issue resolution, and audit-sensitive processes.
Strategic Thinking: Aligns architecture and engineering choices to business outcomes, reuse, governance, security, performance, and long-term maintainability.
Mentorship: Develops engineers and analysts through SQL quality, modeling standards, documentation, testing, and support readiness.
Change Management: Helps teams adopt new data patterns, cloud practices, governance expectations, and proactive production support behaviors.

Additional Information

Location: Springdale, AR (onsite)
Work shift: 1ST SHIFT (United States of America)
Relocation assistance eligible: No
Hourly applicants only: Complete the task after submitting the application to provide additional information to be considered for employment.
Unsolicited assistance: Tyson Foods and its subsidiaries do not accept unsolicited support from external recruitment vendors for open positions within the United States.
Unsolicited resumes: Any resumes or candidate profiles submitted by recruitment vendors or headhunters without valid written request and search agreement approved by HR will be considered the property of Tyson Foods.
No fees: No fees will be paid if the candidate is hired due to an unsolicited referral.

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