Data and Analytics Manager

ABOUT US Seaboard Overseas and Trading Group (SOTG), a division of the Fortune 500 Seaboard Corporation, is a globally integrated leader in agricultural commodity trading, processing, and logistics. With milling facilities in 14 locations across 10 countries and 10 trading offices in 9 countries, we produce approximately two million metric tons of grain-based products annually. Our vertically integrated approach-spanning procurement, transportation, and processing-ensures quality, consistency, and supply chain efficiency. We manage bulk freight and chartered vessels, overseeing logistics for both in-house and third-party customers. Every year, we source, transport, and market around 14 million metric tons of diverse commodities, supporting food security and economic growth in the regions we serve. At SOTG, we are driven by innovation, collaboration, and sustainability. Our business model fosters an entrepreneurial mindset, empowering our teams to take ownership, find creative solutions, and drive impact. GENERAL PURPOSE The Data & Analytics Manager is the operational and people leader of a centralized, globally scoped data function. This role sits between senior leadership and a small but high-impact technical team and is responsible for translating business strategy into data priorities, delivering reliable analytics and reporting services across all departments, and building a global network of embedded Data Champions who extend the team's reach into regional offices worldwide. This is not a purely technical role, nor is it purely managerial. The right person is a credible data practitioner who has grown into leadership. Someone who can review a data model in the morning, present to management in the afternoon, and coach a junior analyst at the end of the day. At this team size, the manager must be both a strategic operator and a hands‑on contributor. DUTIES AND RESPONSIBILITIES Team Leadership & Development Lead, mentor, and develop a close-knit data team Conduct regular 1:1s focused on performance, growth, and wellbeing Set clear goals and success metrics for each team member, aligned to organizational priorities Identify skills gaps and create development plans to address them Foster a team culture of curiosity, rigor, and psychological safety Advocate for team capacity, tooling, and headcount as the function scales Delivery & Prioritization Own the team's intake and prioritization process - ensuring the right work gets done in the right order Run a lightweight agile or sprint-based delivery model suited to a small, globally‑facing team Balance reactive business requests with proactive investment in platform quality and AI readiness Maintain a visible roadmap that communicates priorities and timelines to stakeholders Escalate resourcing conflicts and tradeoff decisions to the VP / Director with clear recommendations Stakeholder Management Serve as the primary point of contact for data and analytics needs across all business units Build trusted relationships with department heads, regional leaders, and senior executives Translate business questions into analytical briefs and data requirements for the technical team Communicate findings, limitations, and recommendations in clear, non‑technical language Proactively surface data insights to stakeholders who may not know to ask for them Data Champion Network Own the design, launch, and ongoing operation of the global Data Champion program Define the champion selection criteria and work with regional leaders to identify candidates Develop and deliver the champion onboarding and certification curriculum Run the biweekly champion sync and quarterly capability workshops Conduct monthly quality audits of champion‑produced content Advocate for champion recognition within their home business units Maintain the champion network documentation, training library, and internal data catalog Scale the network thoughtfully as the organization grows - including regional lead appointments Data Governance & Standards Define and enforce enterprise data standards - metric definitions, naming conventions, certification criteria Maintain a tiered content model (certified vs. community) in the BI platform Work with the Data Engineer to establish and monitor data quality frameworks Ensure compliance with data privacy regulations across all regions of operation Own the data dictionary and ensure it stays current and accessible to champions and stakeholders AI & Analytics Strategy Partner with the VP / Director to develop and execute the data roadmap in support of AI initiatives Ensure the team's data infrastructure work is aligned to AI readiness requirements Evaluate new tools, platforms, and methodologies and make recommendations for adoption Represent the data function in cross‑functional AI and technology planning discussions Collaborate with VP / Director on building the internal case for future headcount (e.g., AI/ML Engineer) with data‑backed justifications Reporting & Impact Measurement Publish a monthly global data health report covering team output, champion activity, and data quality metrics Track and communicate the business impact of the data function to senior leadership Monitor platform usage across the organization and use it to guide enablement priorities Contribute to the annual planning process with capacity analysis and investment recommendations EDUCATION AND EXPERIENCE Bachelor's Degree in Business/IT/Data Analytics Required, Master's Degree in Data Analytics/Science or Statistics preferred. 5+ years of experience in data analytics, business intelligence, or a related field 2+ years in a leadership role within a data function Proven ability to translate business requirements into analytical deliverables Strong working knowledge of BI platforms (AWS, Power BI, Fabric, Tableau, Looker, Alteryx, or equivalent) Proficiency in SQL; comfort reviewing and guiding work in Python or R Demonstrated experience managing stakeholder relationships across multiple departments or regions OTHER QUALIFICATIONS Experience in a globally distributed organization with operations across multiple time zones Familiarity with modern data stack tooling (dbt, Airflow, Snowflake, BigQuery, or equivalent) Exposure to machine learning, AI platforms, or predictive analytics workflows Experience building enablement programs - training, certification, or data literacy initiatives Background in organizational change management or data culture transformation Fluency in a second language is an advantage given the global scope of the role #J-18808-Ljbffr