Top Tech Jobs & Startup Jobs

Reviews and imports billing data, reconciles invoices against operational documentation, processes deposits and cash applications, and investigates discrepancies. The role analyzes billing information, improves data quality, trains cross-functional teams, and responds to client questions about invoices and account balances. It requires strong accuracy, analytical ability, communication, organization, and deadline management in an onsite environment.

Own the lifecycle of AI-enabled products for enterprise functions, from opportunity discovery and business-case development through roadmap prioritization, delivery, adoption, measurement, and iteration. Partner with business and technical stakeholders to define requirements, assess data readiness and risks, guide AI solutions into production, and drive organizational change through communication, training, and feedback.

Leads and develops a software engineering team while remaining hands-on with architecture, technical strategy, coding, debugging, quality, and delivery. Drives Agile practices, manages capacity and priorities, reduces technical debt, establishes engineering standards, evaluates technologies, and partners with Product, Design, Business, and Engineering stakeholders. The role also includes recruiting, mentoring, stakeholder communication, and delivering mobile, cloud, connected, and offline-first applications.

Designs and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, and SQL. Supports SQL Server, SSIS, SSRS, Azure, data warehousing, reporting, analytics, and AI/ML workloads. Responsibilities include optimizing performance and reliability, implementing data quality controls, integrating enterprise data sources, modernizing platforms, and partnering with business and IT teams to deliver scalable data solutions.

Lead the design, development, deployment, and monitoring of production AI/ML applications for dairy-farm intelligence. Responsibilities include data wrangling, feature engineering, model selection, experimentation, MLOps, agent evaluation, observability, fine-tuning, AI governance, and integration with cloud infrastructure. The role also drives AI adoption, establishes engineering practices, collaborates cross-functionally, and may build React and TypeScript user experiences.

Designs, develops, and maintains Databricks-based ETL pipelines, data integration solutions, data warehouses, and reporting datasets. Builds batch and streaming architectures using Python, Spark, SQL, and Delta Lake; optimizes performance and costs; migrates legacy SSIS and SQL Server processes; maintains SSRS reports; implements data quality controls; and collaborates with business and technical teams supporting analytics and AI/ML workloads.

Leads the strategy, roadmap, governance, configuration, integrations, and optimization of Oracle HCM Cloud and connected People applications. Partners with HR, Finance, Digital, Security, and global stakeholders to prioritize enhancements, manage releases, ensure data quality and compliance, oversee testing and adoption, and drive automation using AI/ML. Mentors application analysts and promotes scalable, sustainable platform standards.

Supports month-end reporting, capital expense and fixed asset processes, fleet lease tracking, journal entries, accruals, reconciliations, financial statement analysis, annual audit coordination, accounts payable backup, and IRS 1099/1096 reporting. Collaborates with internal departments and assists accounting leadership with financial inquiries and process improvement.

Coordinate domestic and international shipments of semen and embryos, managing order fulfillment from receipt through invoicing. Responsibilities include inventory management, export documentation, import/export compliance, product receipt verification, logistics coordination, customer service tracking, issue resolution, and supply chain performance monitoring. The role also identifies process improvements and collaborates with clients, production centers, and external partners.

Analyze manufacturing costs, COGS, inventory, margins, variances, and operational drivers. Improve costing, reporting, dashboards, and financial processes while supporting budgeting, forecasting, scenario planning, CAPEX, product economics, and make-versus-buy decisions. Partner with finance, production, R&D, product, and innovation teams to translate complex financial and production data into actionable recommendations.