Data and Analytics Manager

Job DescriptionABOUT USSeaboard 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 PURPOSEThe 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 RESPONSIBILITIESTeam Leadership & DevelopmentLead, mentor, and develop a close-knit data team Conduct regular 1:1s focused on performance, growth, and wellbeingSet clear goals and success metrics for each team member, aligned to organizational prioritiesIdentify skills gaps and create development plans to address themFoster a team culture of curiosity, rigor, and psychological safetyAdvocate for team capacity, tooling, and headcount as the function scalesDelivery & PrioritizationOwn the team's intake and prioritization process — ensuring the right work gets done in the right orderRun a lightweight agile or sprint-based delivery model suited to a small, globally-facing teamBalance reactive business requests with proactive investment in platform quality and AI readinessMaintain a visible roadmap that communicates priorities and timelines to stakeholdersEscalate resourcing conflicts and tradeoff decisions to the VP / Director with clear recommendations Stakeholder ManagementServe as the primary point of contact for data and analytics needs across all business unitsBuild trusted relationships with department heads, regional leaders, and senior executivesTranslate business questions into analytical briefs and data requirements for the technical teamCommunicate findings, limitations, and recommendations in clear, non-technical languageProactively surface data insights to stakeholders who may not know to ask for themData Champion NetworkOwn the design, launch, and ongoing operation of the global Data Champion programDefine the champion selection criteria and work with regional leaders to identify candidatesDevelop and deliver the champion onboarding and certification curriculumRun the biweekly champion sync and quarterly capability workshopsConduct monthly quality audits of champion-produced contentAdvocate for champion recognition within their home business unitsMaintain the champion network documentation, training library, and internal data catalogScale the network thoughtfully as the organization grows — including regional lead appointmentsData Governance & StandardsDefine and enforce enterprise data standards — metric definitions, naming conventions, certification criteriaMaintain a tiered content model (certified vs. community) in the BI platformWork with the Data Engineer to establish and monitor data quality frameworksEnsure compliance with data privacy regulations across all regions of operationOwn the data dictionary and ensure it stays current and accessible to champions and stakeholdersAI & Analytics StrategyPartner with the VP / Director to develop and execute the data roadmap in support of AI initiativesEnsure the team's data infrastructure work is aligned to AI readiness requirementsEvaluate new tools, platforms, and methodologies and make recommendations for adoptionRepresent the data function in cross-functional AI and technology planning discussionsCollaborate with VP / Director on building the internal case for future headcount (e.g., AI/ML Engineer) with data-backed justificationsReporting & Impact MeasurementPublish a monthly global data health report covering team output, champion activity, and data quality metricsTrack and communicate the business impact of the data function to senior leadershipMonitor platform usage across the organization and use it to guide enablement prioritiesContribute to the annual planning process with capacity analysis and investment recommendationsEDUCATION AND EXPERIENCEBachelor’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 field2+ years in a leadership role within a data functionProven ability to translate business requirements into analytical deliverablesStrong 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 RDemonstrated experience managing stakeholder relationships across multiple departments or regionsOTHER QUALIFICATIONSExperience in a globally distributed organization with operations across multiple time zonesFamiliarity with modern data stack tooling (dbt, Airflow, Snowflake, BigQuery, or equivalent)Exposure to machine learning, AI platforms, or predictive analytics workflowsExperience building enablement programs — training, certification, or data literacy initiativesBackground in organizational change management or data culture transformationFluency in a second language is an advantage given the global scope of the role