• Lead end-to-end data migration for MES implementations, upgrades, or consolidations (legacy MES → new MES, ERP → MES, or MES consolidation projects) • Perform detailed source-to-target data mapping for manufacturing-critical entities: BOMs, routings, work instructions, material masters, equipment, process parameters, quality specs, genealogy/traceability data, production history, as-built records, etc. • Design and execute data extraction, transformation, and load (ETL) processes specific to MES platforms • Build and maintain complex data migration scripts, transformation rules, staging tables, and validation frameworks • Lead data cleansing, enrichment, harmonization, and defect resolution activities in collaboration with manufacturing, quality, and engineering teams • Perform MES integration and data synchronization design & implementation (master data, production orders, material movements, quality results, etc.) • Support cutover planning, dry runs, mock go-lives, and hypercare for data migration and integration scope • Conduct data validation, reconciliation, and business sign-off at multiple stages (pre-load, post-load, post-go-live) • Translate manufacturing business rules and production processes into precise data transformation logic and validation criteria • Troubleshoot complex data-related issues during migration, integration, and go-live phases • Create and maintain high-quality migration documentation: mapping spreadsheets, transformation rules, validation scripts, cutover checklists, issue logs • Collaborate closely with MES configuration teams, SAP functional teams, manufacturing SMEs, and quality assurance groups

• Work on a variety of impactful customer technical projects - inclusive of implementation, troubleshooting configurations, instilling best practices, and solutioning MVPs and long term solutions to customer specific requirements • Consult on architecture and design • Ensure our most strategic enterprise customers are adopting the product • Collaborate with other internal customer facing teams at dbt Labs - Sales, Solution Architects, Training, Support • Provide critical feedback to dbt Labs product and engineering teams to improve and prioritize customer requests and ensure rapid resolution for engagement specific issues • Become a product expert with dbt in the context of the modern data stack (if you aren’t already)

• Contribute to the design of application components and services within AGDATA’s modern .NET ecosystem. • Assist with cloud native design, including serverless workloads (e.g., Azure Functions) and containerized services, under the guidance of senior architects. • Help align application designs with broader solution architecture standards and reference architectures. • Produce concise architecture artifacts—diagrams, lightweight Architecture Decision Records (ADRs), and design notes—to facilitate shared understanding. • Participate in architecture and design reviews; capture feedback and incorporate improvements. • Collaborate with engineering teams to shape nonfunctional requirements (NFRs) such as performance, reliability, observability, security, and cost efficiency. • Apply secure design and development practices (identity and access, least privilege, common vulnerability awareness) and support threat modeling discussions. • Contribute to integration patterns, data flows, and cross-system interactions (REST and event driven). • Participate in code reviews with a focus on maintainability, reliability, performance, scalability, and security. • Provide hands-on prototyping and coding for complex or high-impact technical problems. • Work closely with product owners, engineering leads, developers, and DevOps to support iterative delivery and measurable outcomes. • Document patterns and practices; share learnings in brownbags, design sessions, or internal forums. • Adopt and encourage effective use of modern tooling (testing, CI/CD, observability, and documentation) to improve quality and speed.

• Engage with CFO, FP&A, and business stakeholders to gather financial reporting and analytics requirements • Translate business objectives into scalable data and reporting solutions • Identify root-cause data challenges impacting financial insights and decision-making • Design and implement Microsoft Fabric architectures, including Lakehouse, Warehouse, and semantic models • Establish scalable data modeling frameworks and governance standards • Architect end-to-end financial analytics solutions aligned to executive reporting needs • Assess the current data landscape and identify gaps in data quality, structure, and integration • Perform hands-on data extraction, transformation, and cleansing using Microsoft Fabric, SQL, and PySpark • Build and optimize Power BI semantic models and advanced DAX measures • Develop executive dashboards and financial performance reporting solutions