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Vista-backed brand, popular lead data title, and broad cross-cloud/ML requirements create moderate applicant competition.
Core data engineering skills transfer well, but multi-tenant, hybrid AI, and manufacturing ERP needs increase domain specificity.
Explicit 10+ years, 3+ years lead experience, and mandatory data platform/cloud skills make filters strict.
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Own the end-to-end architecture and scalability of the Amtech Cloud Data Platform (ACDP), including data warehouses, tenant data stores, lakes, and feature stores for analytics, ML, and AI agent use cases.
Lead and govern multi-tenant AI Agent data layers, including tenant registries, data classification, routing rules for hybrid AI, and data security/governance across cloud, hybrid, and on-prem tiers.
Provide technical leadership by setting engineering standards, mentoring data engineers, managing pipeline automation/reliability, and partnering with architecture and product stakeholders on platform roadmap.
Bachelor's degree in Computer Science, Software Engineering, or related discipline.
10+ years of experience in data engineering or software development, with at least 3 years in a technical lead or architect role.
Expertise in data warehousing solutions such as Snowflake, Redshift, or BigQuery, along with strong programming skills in Python, Java, or Scala.
Hands-on experience with cloud platforms at scale (AWS, Azure, or GCP), orchestration tools (Airflow, dbt, AWS Glue), big data frameworks (Spark, Flink), and streaming tools (Kafka, Kinesis).
Experienced technical leader comfortable managing complex multi-tenant data architectures supporting AI/ML workloads in hybrid cloud and on-prem environments.
Strong bias towards operational excellence with ability to define data governance, security, observability, and data classification standards at platform scale.
Proven capability to bridge engineering and product teams to drive platform roadmap in enterprise software contexts, especially with AI-driven automation and analytics.