Senior IT Data Engineer (RSenior IT Data Engineer PythonSQL (Onsite)

Job Details:

The Senior IT Data Engineers are experts in data streaming building data pipelines that support real-time data refreshes and are cost-optimized for computing resources. They deeply understand data security implementing row-level and column-level security measures. This role typically involves leading the implementation of complex projects using advanced big data technologies and ensuring robust data pipeline orchestration across multiple systems.

Essential Duties and Responsibilities

• Own and drive the overall data strategy including the multi-quarter technical roadmap platform architecture and data engineering standards.

• Architect end-to-end data solutions across cloud platforms (AWS GCP or Azure) setting standards for orchestration (AirflowDagster) transformation (dbt) streaming (Kafka Flink) and storage (Delta Lake Iceberg Snowflake BigQuery).

• Own the enterprise data modeling strategy crafting scalable models using dimensional multi-dimensional and advanced normalization techniques with enterprise-wide documentation and metadata governance.

• Define API design standards and data contracts to ensure reliable well-governed interfaces between data producers and consumers.

• Establish enterprise-level data governance security and compliance frameworks across all data and AI systems including access controls cataloging and lineage.

• Define and enforce CI/CD standards for data pipelines containerized architectures (Docker K8s) andinfrastructure ascode (Terraform).

• Drive data observability practices and platform reliability at enterprise scale.

• Drive build-vs-buy evaluations for data and AI tools considering TCO vendor lock-in scalability and organizational fit; manage vendor relationships.

• Own or co-own infrastructure budget and capacity planning for data platformresources;optimizecloud costs at the organizational level.

• Define and drive the organizations agentic AI strategy architecting enterprise- scalemulti-agent systems autonomous data pipelines and RAG/knowledge graph platforms.

• Establish AI governance frameworks including ethics policies bias detection safety guardrails security standards (prompt injection data exfiltration PII) and compliance with emerging regulations (e.g. EU AI Act).

• EstablishLLMOpspractices at scale model deployment prompt versioning A/B testing performance monitoring drift detection and cost optimization.

• Design human-in-the-loop escalation paths for critical AI-driven decisions ensuringappropriate oversight.

• Lead AI platform evaluation and integration including TCO analysis data residency and SLA requirements for agentic frameworks.

• Set software engineering best practices code review standards design patterns technical debt management and documentation.

• Advocate for and lead adoption of data mesh and data-as-a-product principles.

• Mentor the engineering team on data engineering data modeling and AI best practices.

• Perform other assigned job-related duties that align with our organizations vision mission and values and fall within your scope of practice.

Qualifications

Education:Bachelors Degree or relevant experience.

Preferred Certification(s):AWS Solutions Architect Professional Google Professional

Data Engineer Azure Solutions Architect Expert Databricks Certified Data Engineer

Professional or equivalent.

Experience:3 years of relevant and practical experience.

Special Skills

• Expertproficiencyin Python and SQL for data engineering at scale.

• Expertisein modern data platforms (Databricks Snowflake BigQuery)lakehousearchitectures(Delta Lake Iceberg) and streaming (Kafka Flink Pub/Sub).

• Deepexpertisein at least one major cloud platform with cross-cloud awareness.

• Mastery of orchestration transformation (dbt) containerization (Docker K8s) andIaC(Terraform).

• Advanced enterprise data modeling warehousing data contracts and API design.

• Expertisein CI/CD data observability governance data mesh and platform reliability.

• Experience in technical roadmap ownership build-vs-buy evaluation and budget/capacity planning.

• Expert-level knowledge of agentic AI architecturesLLMOps RAG knowledge graphs and AI governance/safety/security.

Soft Skills

• Leadership:Owning and driving data and AI strategy across the organization.

• Strategic Vision:Translating businessobjectivesinto actionable technical roadmaps.

• Stakeholder Management:Building relationships with partners and executive leadership.

• Communication:Presenting complex data and AI concepts to board-level audiences.

• Mentorship:Developing the data engineering teams data and AI competencies.

• Decision-Making:Making high-impact choices on architecture platforms and investments.

• Change Management:Guiding the organization through data and AI transformations.

• Innovation & Thought Leadership:Driving industry best practices in data engineering modeling and agentic AI.

• Negotiation:Balancing technical requirements with business needs and resource constraints.

**Not eligible for visa sponsorship **

** Not eligible for relocation assistance **

Relocation Assistance Eligible:

Work Shift:

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.

Hourly Applicants ONLY -You must complete the task after submitting your application to provide additional information to be considered for employment.

The successful candidate(s) must be willing and able to perform the physical requirements of the job with or without a reasonable accommodation.

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.

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.

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