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, Vistas 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.

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.

- Own end-to-end architecture for ACDP: data warehouses, tenant data stores, lakes, and feature stores supporting analytics, ML, and AI agent use cases.
- Design and build the tenant registry and tenant data warehouse layer that underpins multi-tenant AI Agent workloads.
- Build and govern the Data Agent layer that supplies on-prem/customer-controlled data to cloud LLM reasoning in the Hybrid AI zone, with staged, explainable data outputs and human review checkpoints.
- Define data classification and routing rules that determine which data can flow to Cloud AI, which requires the Hybrid AI path, and which must remain fully on-prem/deterministic — protecting customer IP and production-critical logic.
- Set engineering standards for ETL/ELT design, orchestration, and data quality across the team.
- Lead design and code reviews; mentor data engineers and act as technical escalation point.
- Drive automation and reliability of pipelines, including SLAs, observability, and incident response.
- Own data security, access control, lineage, and governance compliance at the platform level, across cloud, hybrid, and on-prem tiers.
- Partner with data scientists and analysts to ensure platform data is ML-ready and supports predictive modeling.




- Build and maintain the data/event pipelines connecting ERP source systems (e.g., EnCore) to the EnCore Agent Hub, supporting secure read/write and event-and-trigger flows.
- Guide GenAI/LLM data enablement, including embeddings, vector database design, and RAG pipeline architecture, in support of Amtech AI Cloud agent orchestration.
- Represent data engineering in cross-functional architecture (ARB) and platform roadmap discussions.
- Optimize pipelines for low-latency access; establish partitioning, caching, and indexing strategies as team standards.

Qualifications

- Bachelor's degree in Computer Science, Software Engineering, or related discipline.
- 10+ years of experience in data engineering or software development, including 3+ years in a technical lead or architect capacity.
- Deep expertise in data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
- Strong programming skills in Python, Java, or Scala.
- Proven experience with orchestration tools (e.g., Airflow, dbt, AWS Glue).
- Hands-on ownership of cloud platforms at scale (AWS, Azure, or GCP), plus familiarity with on-prem/private deployment models.
- Proficiency with big data frameworks (e.g., Spark, Flink) and streaming tools (Kafka, Kinesis).
- Expert-level SQL and NoSQL databases; familiarity with time-series or graph databases is a plus.
- Experience setting data validation, governance, and observability standards (e.g., Great Expectations, Prometheus, Grafana).
- Demonstrated experience mentoring engineers or leading a technical team.
- Experience designing multi-tenant data architectures (tenant registries, tenant-scoped data stores/warehouses) is a strong plus.
- Understanding of data sensitivity/risk classification and hybrid cloud/on-prem routing for AI workloads is a robust plus.

Preferred Qualifications

- Advanced training in Data Engineering, Cloud Architecture, or Industrial Data Systems.
- Experience with ERP, MES, or manufacturing data environments.
- Familiarity with IoT/OT data pipelines, including machine telemetry and SCADA signals.
- Applied experience with GenAI tools such as LangChain, vector databases, and RAG pipelines in production.
- Exposure to agent orchestration platforms, MCP-style tool routing, or event-driven agent architectures.
- Experience building or governing hybrid AI architectures balancing cloud acceleration with on-prem/private control layers.

📌 Lead Data Engineer (Bengaluru)
🏢 Amtech
📍 Bengaluru