• Design and implement data and application integrations using Boomi, APIs, and event-driven patterns • Build and manage secure, scalable integrations across enterprise platforms including ERP, CRM, operational systems, and data platforms • Monitor, troubleshoot, and optimize integration workflows for reliability and performance • Extract, transform, and model structured and semi-structured data for analytics and downstream consumption • Implement and manage data storage solutions including data lakes, data warehouses, and curated data marts • Partner with architects, data scientists, and business teams to design solution patterns that support AI and automation use cases • Enable AI solutions by engineering clean, well-integrated, and governed data inputs • Build and manage automated data and integration pipelines delivering consistent outcomes • Contribute to technical documentation, operational runbooks, and knowledge sharing

• Define and lead enterprise data strategy, aligning business goals, data architecture, and AI/ML adoption • Design and implement modern cloud data platforms (lakehouse, data warehouse, streaming architectures) • Establish and enforce data architecture standards • Own and define enterprise data governance frameworks, including data ownership, stewardship, lineage, metadata, and data quality standards • Establish data management operating models and governance processes across business and engineering teams • Design and build scalable, reliable, and high-performance data pipelines • Optimize data platforms for performance, scalability, and cost efficiency • Ensure data quality, consistency, and accessibility across all data layers • Enable AI-ready data platforms, ensuring governed, traceable, and high-quality datasets for analytics and ML • Conduct data maturity assessments and define transformation roadmaps • Lead client workshops, architecture discussions, and pre-sales engagements • Create and present solution architectures, proposals, and technical strategies • Act as a trusted advisor to C-level stakeholders and engineering teams • Develop reference architectures, best practices, and reusable assets • Mentor engineers and contribute to building a high-performing data engineering and architecture capability

• Engage with retail clients to understand their store operations, backend systems, and data requirements. • Define end-to-end integration strategies, including data ingestion, pre and post processing, and publishing to relevant retail systems. • Serve as the subject matter expert on Simbe’s products and offerings, including APIs, mobile apps, and business intelligence tools. • Develop pilot use cases and demos showcasing Tally’s data capture, analytics, and integration with client’s systems. • Guide the implementation process, working with internal Simbe deployment teams and client technical teams to configure integrations. • Partner with Customer Success and Product teams to build robust adoption strategies, including user training, documentation, and onboarding processes. • Act as the technical point of contact for key stakeholders, maintaining a proactive communication channel for support.

• Lead and manage global RFx response efforts (RFPs, RFIs, security questionnaires), ensuring alignment across sales, presales, and product teams and own the end-to-end RFx process — from intake and planning through to submission. • Act as a central point of contact for all technical content development, ensuring accuracy, consistency, and messaging alignment across product areas such as integration & Automation, API Management, Data Management, AI Management, etc. • Work cross-functionally with sales engineers, security, legal, and product SMEs to gather, curate, and update technical content used in proposals. • Track and report on key metrics, bottlenecks, and areas for improvement across technical content development and delivery processes, driving continuous optimization. • Maintain and evolve a library of standard responses, templates, and reusable technical assets for solutions and proposals. • Design scalable and reusable integration solutions by aligning customer business strategies with technical capabilities, collaborating closely with field solution engineers and presales teams. • Drive technical validation through architecture reviews, feasibility assessments, and proof-of-concepts to ensure proposed integration solutions meet established standards.