Data Engineer

**About Vista Equity Partners
**Vista Equity Partners is a leading global investment firm focused exclusively on enterprise software, data, and technology-enabled businesses. With over $100B in assets under management and a portfolio of 90+ software product companies worldwide, Vista accelerates growth through operational excellence, shared expertise, and long-term partnership. In India, Vista’s presence continues to expand with 45+ portfolio companies employing more than 17,000 professionals across technology, product, customer success, and operations — reinforcing India’s strategic role as a hub of innovation and talent within the Vista ecosystem.
Through its Agentic AI Factory, Vista is embedding Generative AI across its global portfolio — enabling companies to integrate intelligent, responsible AI into products, operations, and decision-making. This initiative is strengthened through portfolio-wide learning programs, leadership workshops, and AI hackathons that foster innovation, build fluency, and accelerate practical AI adoption across teams.

**About Amtech
**Amtech is a leading provider of enterprise software solutions for the packaging, printing, and manufacturing industries. Our integrated systems streamline order management, production planning, scheduling, inventory, and business analytics — empowering customers to drive efficiency, reduce costs, and improve operational performance. With a strong commitment to innovation and customer success, Amtech delivers reliable technology backed by deep industry expertise.

With Vista’s investment and strategic guidance, we combine the agility of a growing technology organization with the scale, stability, and career mobility of a global software ecosystem.

**Our Employee Value Proposition
**At Amtech, our people are our greatest differentiator. We create an environment where you can:

**Purpose
**Shape the future of manufacturing and supply chain operations by delivering mission-critical enterprise software used by industry-leading organizations.

**Growth
**Access continuous learning, leadership development, and cross-portfolio opportunities through Vista’s global network — accelerating both technical and managerial career paths.

**Culture
**Work in a collaborative, transparent, and people-first environment where values, accountability, and integrity guide every decision.

**Innovation
**Engage with cutting-edge technologies, including AI-driven automation, and contribute to modernizing financial systems and operational processes across the business.

**Role Description
**Amtech LLC is seeking a Lead Data Engineer to own the architecture, scalability, and technical direction of ACDP (Amtech Cloud Data Platform) - the data warehouses, pipelines, tenant data stores, and feature stores that power analytics, personalization, and AI agent initiatives across the company. This role combines hands-on engineering with technical leadership: setting standards, mentoring engineers, and partnering with architecture and product stakeholders to shape the platform's roadmap. The Lead Data Engineer will play a central role in building the data foundation behind Amtech's AI Agents initiative — the tenant registries, tenant data warehouses, analytics/monitoring, and event pipelines that feed the Amtech Agent Hub and the broader Amtech AI Cloud. This includes helping stand up the data layer that supports agent use cases and expanding platform capabilities beyond traditional analytics into next-generation, agent-driven intelligence. This role is also central to Amtech's intentional hybrid AI strategy, which routes each use case to the right tier based on risk, data sensitivity, latency, and IP protection. The Lead Data Engineer will build and govern the data layer underneath all three tiers — the stateless Cloud AI acceleration layer, the Hybrid AI zone where cloud LLM reasoning is combined with on-prem data via a Data Agent, and the deterministic On-Prem/Private AI control layer for margin- and production-critical logic — ensuring the org, not the model, controls where sensitive data flows.