Explore 3 python cloud platform developer jobs from 1 hiring companies in Alma, AR, US. Filter by remote, salary, experience, and company, then open any listing to apply.

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Python Cloud Platform Developer

Van Buren

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Fayetteville

Barling

Springdale

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Clarksville

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Python Cloud Platform Developer Jobs

Tyson Foods

Onsite

Internal Management &amp; Management Support Applicants: Automatic notification to your current manager will be initiated upon selection for interview. This applies to all current P or M level candidates.Relocation Assistance Eligible:NoReferral Payout Eligible:YesContinue growing with our family. Our team members make it happen. If you want to continue to grow in a new role internally and see a position that looks right for you, we encourage you to apply! Thanks for your commitment to Tyson Foods. Management Level: P4<div><div>The Lead IT Data Engineer owns and drives the organization&#39;s data strategy, setting the technical direction for data engineering, enterprise data modeling, and agentic AI adoption. This role is responsible for platform architecture, tool selection, cloud strategy, budget and capacity planning, and the design of enterprise AI agent systems — all while establishing governance frameworks for responsible data and AI practices and mentoring the engineering team. </div><div>Essential Duties and Responsibilities </div><div><ul><li>Own and drive the overall data strategy, including the multi-quarter technical roadmap, platform architecture, and data engineering standards. </li></ul></div></div><div><div><ul><li>Architect end-to-end data solutions across cloud platforms (AWS, GCP, or Azure), setting standards for orchestration (Airflow, Dagster), transformation (dbt), streaming (Kafka, Flink), and storage (Delta Lake, Iceberg, Snowflake, BigQuery). </li></ul></div><div><ul><li>Own the enterprise data modeling strategy — crafting scalable models using dimensional, multi-dimensional, and advanced normalization techniques, with enterprise-wide documentation and metadata governance. </li></ul></div><div><ul><li>Define API design standards and data contracts to ensure reliable, well-governed interfaces between data producers and consumers. </li></ul></div><div><ul><li>Establish enterprise-level data governance, security, and compliance frameworks across all data and AI systems, including access controls, cataloging, and lineage. </li></ul></div><div><ul><li>Define and enforce CI/CD standards for data pipelines, containerized architectures (Docker, K8s), and infrastructure as code (Terraform). </li></ul></div><div><ul><li>Drive data observability practices and platform reliability at enterprise scale. </li></ul></div><div><ul><li>Drive build-vs-buy evaluations for data and AI tools, considering TCO, vendor lock-in, scalability, and organizational fit; manage vendor relationships. </li></ul></div><div><ul><li>Own or co-own infrastructure budget and capacity planning for data platform resources; optimize cloud costs at the organizational level. </li></ul></div><div><ul><li>Define and drive the organization&#39;s agentic AI strategy, architecting enterprise- scale multi-agent systems, autonomous data pipelines, and RAG/knowledge graph platforms. </li></ul></div><div><ul><li>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). </li></ul></div><div><ul><li>Establish LLMOps practices at scale — model deployment, prompt versioning, A/B testing, performance monitoring, drift detection, and cost optimization. </li></ul></div><div><ul><li>Design human-in-the-loop escalation paths for critical AI-driven decisions, ensuring appropriate oversight. </li></ul></div><div><ul><li>Lead AI platform evaluation and integration, including TCO analysis, data residency, and SLA requirements for agentic frameworks. </li></ul></div><div><ul><li>Set software engineering best practices — code review standards, design patterns, technical debt management, and documentation. </li></ul></div><div><ul><li>Advocate for and lead adoption of data mesh and data-as-a-product principles. </li></ul></div><div><ul><li>Mentor the engineering team on data engineering, data modeling, and AI best practices. </li></ul></div><div><ul><li>Perform other assigned job-related duties that align with our organization&#39;s vision, mission, and values and fall within your scope of practice. </li></ul></div><div>Qualifications </div><div>Education: Bachelor&#39;s Degree or relevant experience. </div><div>Preferred Certification(s): AWS Solutions Architect Professional, Google Professional </div></div><div><div>Data Engineer, Azure Solutions Architect Expert, Databricks Certified Data Engineer </div><div>Professional, or equivalent. </div><div>Experience: 5&#43; years of relevant and practical experience. </div><div>Special Skills </div><div><ul><li>Expert proficiency in Python and SQL for data engineering at scale. </li></ul></div><div><ul><li>Expertise in modern data platforms (Databricks, Snowflake, BigQuery), lakehouse architectures (Delta Lake, Iceberg), and streaming (Kafka, Flink, Pub/Sub). </li></ul></div><div><ul><li>Deep expertise in at least one major cloud platform with cross-cloud awareness. </li></ul></div><div><ul><li>Mastery of orchestration, transformation (dbt), containerization (Docker, K8s), and IaC (Terraform). </li></ul></div><div><ul><li>Advanced enterprise data modeling, warehousing, data contracts, and API design. </li></ul></div><div><ul><li>Expertise in CI/CD, data observability, governance, data mesh, and platform reliability. </li></ul></div><div><ul><li>Experience in technical roadmap ownership, build-vs-buy evaluation, and budget/capacity planning. </li></ul></div><div><ul><li>Expert-level knowledge of agentic AI architectures, LLMOps, RAG, knowledge graphs, and AI governance/safety/security. </li></ul></div><div>Soft Skills </div><div><ul><li>Leadership: Owning and driving data and AI strategy across the organization. </li></ul></div><div><ul><li>Strategic Vision: Translating business objectives into actionable technical roadmaps. </li></ul></div><div><ul><li>Stakeholder Management: Building relationships with partners and executive leadership. </li></ul></div><div><ul><li>Communication: Presenting complex data and AI concepts to board-level audiences. </li></ul></div><div><ul><li>Mentorship: Developing the data engineering team&#39;s data and AI competencies. </li></ul></div><div><ul><li>Decision-Making: Making high-impact choices on architecture, platforms, and investments. </li></ul></div><div><ul><li>Change Management: Guiding the organization through data and AI transformations. </li></ul></div></div><div><div><ul><li>Innovation &amp; Thought Leadership: Driving industry best practices in data engineering, modeling, and agentic AI. </li></ul></div><div><ul><li>Negotiation: Balancing technical requirements with business needs and resource constraints. </li></ul>** Not eligible for visa sponsorship now or in the future **** Not eligible for relocation assistance **</div></div>Work Shift:1ST SHIFT (United States of America)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.<div><div><div><div><div><div><div><div><div><div><div><div><div><div>CCPA Notice. If you are a California resident, and would like to learn more about what categories of personal information we collect when you apply for this job, and how we may use that information, please read our CCPA Job Applicant Notice at Collection, <a href="https://www.tysonfoods.com/sites/default/files/2020-07/CCPA%20applicant%20notification.pdf" target="_blank">click here</a>.</div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Lead IT Data Engineer (SQL/Python)

Lead IT Data Engineer

5+ years of data engineering experience; strong Python and SQL; cloud data platforms; governance and AI/ML focus; leadership.

Internal Management &amp; Management Support Applicants: Automatic notification to your current manager will be initiated upon selection for interview. This applies to all current P or M level candidates.Relocation Assistance Eligible:NoReferral Payout Eligible:NoContinue growing with our family. Our team members make it happen. If you want to continue to grow in a new role internally and see a position that looks right for you, we encourage you to apply! Thanks for your commitment to Tyson Foods. Management Level: P5<div>Job Summary </div><div>Tyson Foods is seeking a highly skilled and business-oriented Data Engineer III to join our Enterprise Asset Management (EAM) organization. This role is responsible for advancing enterprise asset data strategies that optimize the full lifecycle management of manufacturing equipment, facilities, and infrastructure from design and construction through commissioning, operation, maintenance, and decommissioning. </div><div>The Data Engineer III will operate across three integrated functional domains: Finance &amp; Accounting, Application Development &amp; Configuration, and Master Data Governance. This position serves as a critical bridge between business operations, finance, engineering, maintenance, and IT teams to ensure enterprise asset data is accurate, actionable, governed, and aligned to strategic objectives.  This role requires a professional who can successfully balance day-to-day functional responsibilities with long-term strategic improvement initiatives ensuring operational support needs are met while continuously modernizing processes, systems, data quality, and business capabilities. </div><div>This role will leverage advanced capabilities within SAP S/4HANA RISE Private Cloud (FICO, PM, PS, MM, EHS with Fiori UI/UX), Google Cloud Platform (GCP) or equivalent cloud data environments, Collibra or equivalent data governance platforms, and visualization/analytics solutions including Power BI, Palantir, Analysis for Excel, or equivalent business intelligence and analytics tools as well as AI-enabled development tools utilizing market-leading LLM technologies or equivalent solutions. </div><div>The ideal candidate combines strong technical data engineering skills with asset-intensive business process knowledge, financial acumen, ERP configuration experience, enterprise data governance expertise, and the ability to lead complex cross-functional initiatives that improve operational reliability, capital efficiency, and governance maturity. </div><div>Essential Duties and Responsibilities </div><div>Finance &amp; Accounting / Property Management </div><ul><li><div>Support enterprise asset accounting processes including Construction in Progress (CIP), fixed asset capitalization, Maintenance &amp; Repair (M&amp;R) posting accuracy, reconciliation, and lifecycle cost management across multiple facilities.  </div></li><li><div>Partner with Finance, Controlling, Engineering, and Operations teams to improve cost transparency, depreciation drivers, asset utilization, and educate stakeholders on property governance and total cost of ownership (TCO).  </div></li><li><div>Develop dashboards and analytics using Power BI, Palantir, or equivalent tools to evaluate M&amp;R performance, MRO inventory vs. replacement asset value (RAV), and cost optimization opportunities, incorporating engineered life drivers such as utilization, operating conditions, criticality, complexity, and maintenance demand. </div></li><li><div>Develop and maintain 5-year M&amp;E CAPEX forecasts based on standardized engineered life assumptions with calculated replacement asset value (RAV) supporting capital planning, prioritization, and procurement price negotiation strategies. </div></li><li><div>Support audits, litigation requests, acquisitions, divestitures, plant closures, and due diligence, while maintaining governed financial data lineage, ownership, and controls through Collibra or equivalent platforms.  </div></li></ul><div>Application Development, ERP Configuration &amp; Systems Integration </div><ul><li><div>Serve as a key partner in the design, enhancement, support, and configuration of SAP EAM-related processes within SAP S/4HANA, balancing production support needs with long-term roadmap execution.  </div></li><li><div>Collaborate with IT and third parties to integrate SAP with connected systems including data lakes, maintenance platforms, procurement tools, governance platforms, and analytics technologies or equivalent solutions.  </div></li><li><div>Design, build, and optimize data pipelines into GCP or equivalent cloud environments, ensuring trusted enterprise reporting, data availability, and scalable analytics capabilities.  </div></li><li><div>Develop UI/UX tools, automation solutions, low-code applications, self-service workflows, AI-assisted capabilities, and predictive asset insights that simplify user interaction and improve capital planning decisions.  </div></li></ul><div>Master Data Governance &amp; Data Quality </div><ul><li><div>Define and maintain enterprise standards for asset master data, equipment hierarchies, functional locations, cost structures, metadata, naming conventions, and business glossary definitions.  </div></li><li><div>Administer or partner with governance teams to maintain Collibra or equivalent platforms including catalogs, dictionaries, lineage, stewardship assignments, workflows, ownership models, and policy controls.  </div></li><li><div>Lead cleansing, harmonization, enrichment, and standardization initiatives for legacy and active asset data while balancing daily support requirements with long-term governance maturity goals.  </div></li><li><div>Build data quality scorecards, exception reporting, and analytics to identify duplication, hierarchy gaps, classification issues, and opportunities to improve decision-grade data.  </div></li></ul><div>Strategic Leadership / Collaboration </div><ul><li><div>Lead medium to large cross-functional initiatives with minimal supervision, effectively prioritizing resources between immediate business demands and strategic transformation opportunities.  </div></li><li><div>Translate complex technical findings into clear business recommendations for leadership, finance, engineering, maintenance, and IT stakeholders.  </div></li><li><div>Mentor junior analysts, engineers, and data stewards on best practices in data engineering, governance, analytics, and enterprise asset management processes.  </div></li><li><div>Drive a culture of continuous improvement by staying current on emerging technologies including cloud platforms, ERP modernization, AI/LLM tools, and manufacturing digital trends. </div></li></ul><h2>Requirements: </h2><div>Education: Bachelor’s degree in Engineering, Construction Management, Information Systems, Computer Science, Finance, Supply Chain, or a related field.</div><div>Experience: 5&#43; years of experience spanning data engineering, ERP systems, asset management, finance systems, manufacturing analytics, and/or data governance. </div><div>Computer Skills: Strong applied knowledge of fixed assets, CIP accounting, maintenance processes, reliability, and manufacturing operations in an asset-intensive environment is required along with hands-on experience in SAP S/4HANA (PM, PS, MM, FICO preferred with exposure to Fiori deployment). Demonstrated ability to balance operational support with strategic improvement initiatives is essential. Experience with data governance platforms such as Collibra (or equivalent), cloud/data engineering tools (SQL, Python, ETL/ELT, GCP or equivalent), and analytics platforms such as Power BI, Palantir, Tableau, or Analysis for Excel are expected. Industry experience in manufacturing asset-heavy environments is preferred. </div><div>Supervisory: This is an individual contributor role (no direct supervisory responsibility); however, the position is expected to train, guide, and support junior team members as needed.</div><div>Travel: The role also requires up to 50% travel to manufacturing sites and project locations.</div><div></div><div>This position does not offer sponsorship benefits. Candidate will need to provide resume to be considered for this position.</div>Work Shift:A Shift (United States of America)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.<div><div><div><div><div><div><div><div><div><div><div><div><div><div>CCPA Notice. If you are a California resident, and would like to learn more about what categories of personal information we collect when you apply for this job, and how we may use that information, please read our CCPA Job Applicant Notice at Collection, <a href="https://www.tysonfoods.com/sites/default/files/2020-07/CCPA%20applicant%20notification.pdf" target="_blank">click here</a>.</div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Data Engineer III

5+ years data engineering with ERP, asset management, finance systems; SAP S/4HANA, data governance, cloud platforms; BI/analytics tools.

Job Details:<div><div>The Lead IT Data Engineer owns and drives the organization&#39;s data strategy, setting the technical direction for data engineering, enterprise data modeling, and agentic AI adoption. This role is responsible for platform architecture, tool selection, cloud strategy, budget and capacity planning, and the design of enterprise AI agent systems — all while establishing governance frameworks for responsible data and AI practices and mentoring the engineering team. </div><div>Essential Duties and Responsibilities </div><div><ul><li>Own and drive the overall data strategy, including the multi-quarter technical roadmap, platform architecture, and data engineering standards. </li></ul></div></div><div><div><ul><li>Architect end-to-end data solutions across cloud platforms (AWS, GCP, or Azure), setting standards for orchestration (Airflow, Dagster), transformation (dbt), streaming (Kafka, Flink), and storage (Delta Lake, Iceberg, Snowflake, BigQuery). </li></ul></div><div><ul><li>Own the enterprise data modeling strategy — crafting scalable models using dimensional, multi-dimensional, and advanced normalization techniques, with enterprise-wide documentation and metadata governance. </li></ul></div><div><ul><li>Define API design standards and data contracts to ensure reliable, well-governed interfaces between data producers and consumers. </li></ul></div><div><ul><li>Establish enterprise-level data governance, security, and compliance frameworks across all data and AI systems, including access controls, cataloging, and lineage. </li></ul></div><div><ul><li>Define and enforce CI/CD standards for data pipelines, containerized architectures (Docker, K8s), and infrastructure as code (Terraform). </li></ul></div><div><ul><li>Drive data observability practices and platform reliability at enterprise scale. </li></ul></div><div><ul><li>Drive build-vs-buy evaluations for data and AI tools, considering TCO, vendor lock-in, scalability, and organizational fit; manage vendor relationships. </li></ul></div><div><ul><li>Own or co-own infrastructure budget and capacity planning for data platform resources; optimize cloud costs at the organizational level. </li></ul></div><div><ul><li>Define and drive the organization&#39;s agentic AI strategy, architecting enterprise- scale multi-agent systems, autonomous data pipelines, and RAG/knowledge graph platforms. </li></ul></div><div><ul><li>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). </li></ul></div><div><ul><li>Establish LLMOps practices at scale — model deployment, prompt versioning, A/B testing, performance monitoring, drift detection, and cost optimization. </li></ul></div><div><ul><li>Design human-in-the-loop escalation paths for critical AI-driven decisions, ensuring appropriate oversight. </li></ul></div><div><ul><li>Lead AI platform evaluation and integration, including TCO analysis, data residency, and SLA requirements for agentic frameworks. </li></ul></div><div><ul><li>Set software engineering best practices — code review standards, design patterns, technical debt management, and documentation. </li></ul></div><div><ul><li>Advocate for and lead adoption of data mesh and data-as-a-product principles. </li></ul></div><div><ul><li>Mentor the engineering team on data engineering, data modeling, and AI best practices. </li></ul></div><div><ul><li>Perform other assigned job-related duties that align with our organization&#39;s vision, mission, and values and fall within your scope of practice. </li></ul></div><div>Qualifications </div><div>Education: Bachelor&#39;s Degree or relevant experience. </div><div>Preferred Certification(s): AWS Solutions Architect Professional, Google Professional </div></div><div><div>Data Engineer, Azure Solutions Architect Expert, Databricks Certified Data Engineer </div><div>Professional, or equivalent. </div><div>Experience: 5&#43; years of relevant and practical experience. </div><div>Special Skills </div><div><ul><li>Expert proficiency in Python and SQL for data engineering at scale. </li></ul></div><div><ul><li>Expertise in modern data platforms (Databricks, Snowflake, BigQuery), lakehouse architectures (Delta Lake, Iceberg), and streaming (Kafka, Flink, Pub/Sub). </li></ul></div><div><ul><li>Deep expertise in at least one major cloud platform with cross-cloud awareness. </li></ul></div><div><ul><li>Mastery of orchestration, transformation (dbt), containerization (Docker, K8s), and IaC (Terraform). </li></ul></div><div><ul><li>Advanced enterprise data modeling, warehousing, data contracts, and API design. </li></ul></div><div><ul><li>Expertise in CI/CD, data observability, governance, data mesh, and platform reliability. </li></ul></div><div><ul><li>Experience in technical roadmap ownership, build-vs-buy evaluation, and budget/capacity planning. </li></ul></div><div><ul><li>Expert-level knowledge of agentic AI architectures, LLMOps, RAG, knowledge graphs, and AI governance/safety/security. </li></ul></div><div>Soft Skills </div><div><ul><li>Leadership: Owning and driving data and AI strategy across the organization. </li></ul></div><div><ul><li>Strategic Vision: Translating business objectives into actionable technical roadmaps. </li></ul></div><div><ul><li>Stakeholder Management: Building relationships with partners and executive leadership. </li></ul></div><div><ul><li>Communication: Presenting complex data and AI concepts to board-level audiences. </li></ul></div><div><ul><li>Mentorship: Developing the data engineering team&#39;s data and AI competencies. </li></ul></div><div><ul><li>Decision-Making: Making high-impact choices on architecture, platforms, and investments. </li></ul></div><div><ul><li>Change Management: Guiding the organization through data and AI transformations. </li></ul></div></div><div><div><ul><li>Innovation &amp; Thought Leadership: Driving industry best practices in data engineering, modeling, and agentic AI. </li></ul></div><div><ul><li>Negotiation: Balancing technical requirements with business needs and resource constraints. </li></ul>** Not eligible for visa sponsorship now or in the future **** Not eligible for relocation assistance **</div></div>Relocation Assistance Eligible:NoWork Shift:1ST 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. Hourly Applicants ONLY -You must complete the task after submitting your application to provide additional information to be considered for employment.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.If you would like to learn more about your data privacy rights and how you may use that information, please read our Job Applicant Privacy Notice <a href="https://www.tysonfoods.com/careers" target="_blank">here</a>.Unsolicited 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. No fees will be paid if the candidate is hired due to an unsolicited referral.

Leads data strategy, cloud data platforms, governance, CI/CD for data pipelines, and agentic AI initiatives; 5+ years experience; Python/SQL; Databricks/Snowflake/BigQuery.

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