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ScreenCloud is a cloud-based SaaS platform founded in 2015 that helps businesses drive engagement and sales through digital signage and content management. With 10,000+ customers globally and 100+ employees across Bangkok, Belfast, LA, Charlotte, and London, the company is building AI-powered solutions for enterprise communication.
You will lead ScreenCloud's commercial data platform as Director of Data Engineering, reporting to the VP of Engineering from the Bangkok hub. Your primary customer is the Revenue Operations team, which powers the commercial side of the business. You'll partner closely with the Director of RevOps to design and deliver a data roadmap addressing customer segmentation, net revenue retention (NRR) analysis, and financial forecasting.
In year one, your top priority is establishing rock-solid financials: a trusted commercial data layer that reveals nuance in the customer base, spots trends early, and enables accurate forecasting. Your second mission is building the data foundation for AI—clean, well-governed, well-modeled data that enables AI across the business.
This is a half-leader, half-practitioner role. You'll set direction, build roadmaps with RevOps, present plans to the CFO and CRO, and work hands-on with your team of two: a Staff Engineer in Bangkok and a Senior Engineer in London. You'll own the commercial data platform end-to-end, including the Redshift warehouse, self-built ETL pipelines, and third-party sync tools like Hightouch. You'll consolidate data sources (billing, CRM, product usage, Intercom) into sources of truth, drive the separation of commercial and product data, lead the migration from Tableau to Power BI, and champion data quality and governance.
The role requires strong collaboration with London-based RevOps and commercial teams, with roughly 2 hours of daily overlap (10:00–18:00 Bangkok time). You must be a credible technical leader who can hire, coach, and direct engineers while staying hands-on where it matters. You'll present confidently to senior stakeholders and drive adoption of data-driven decision-making across the organization.
