Data Architect

HMG AMERICA LLC

Massachusetts

On-site

USD 140,000 - 230,000

Full time

3 hours ago
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Job summary

HMG AMERICA LLC seeks a Data Architect specialized in the Databricks ecosystem to design and deliver agentic AI and data platform solutions on AWS and Databricks. You will shape conversational analytics, agent building, and governance across warehouse, lakehouse, and semantic foundations.

The role emphasizes deep Databricks expertise, Genie capabilities, and hands-on development of AI agents, with onsite work in Boston, MA.

Qualifications

  • Experience with Databricks architecture from design to production.
  • Hands-on experience building and evaluating AI agents on AWS and Databricks.
  • Knowledge of Databricks Genie, Genie Ontology, and Genie AI Gateway.
  • Strong grounding in data warehouse, lakehouse modeling and governance.

Responsibilities

  • Architect and deliver data and AI solutions across the Databricks ecosystem.
  • Design and implement conversational analytics using Databricks Genie and Genie Ontology.
  • Build and orchestrate AI agents in AWS and Databricks, validate and evaluate.
  • Implement retrieval and grounding using Databricks Vector Search.
  • Define ontology, knowledge graph, and semantic layer foundations.
  • Architect data warehouse and lakehouse solutions with data modelling.
  • Establish data cataloging practices and maintain business glossary with governance teams.

Skills

Databricks Ecosystem
Databricks Genie
Agentic AI Implementation
AgentBricks & Vector Search
Data Warehouse & Lakehouse
Semantic Foundations
Data Cataloging & Glossary
Atlan

Tools

Atlan

Job description

Role - Data Architect (Databricks and Agentic AI)
Location - Boston, MA (Onsite all 5 days/ week)
ROLE OVERVIEW

We are looking for a Data Architect who is well versed in the Databricks ecosystem and Databricks architecture to design and deliver agentic AI and data platform solutions on AWS and Databricks. The role spans conversational analytics with Databricks Genie, agent building and orchestration, and the warehouse, lakehouse, and semantic foundations that ground these solutions in governed business context.

KEY RESPONSIBILITIES
  • Architect and deliver data and AI solutions across the Databricks ecosystem, applying deep knowledge of Databricks architecture, workspace design, and platform governance.
  • Design and implement conversational analytics using Databricks Genie, including Genie Ontology and the Genie AI Gateway.
  • Build and orchestrate AI agents in the AWS and Databricks ecosystems, then validate them and run structured evaluations before production.
  • Implement retrieval and grounding using Databricks Vector Search and general vector search techniques.
  • Define ontology, knowledge graph, and semantic layer foundations that give agents reliable, governed business context.
  • Architect data warehouse and lakehouse solutions with sound data modelling across layers.
  • Establish data cataloging practices and maintain the business glossary with governance teams.
WHAT WE'RE LOOKING FOR
MUST-HAVE SKILLS

Databricks Ecosystem — Deep expertise in the Databricks ecosystem and architecture, from design through production.

Databricks Genie — Working knowledge of Databricks Genie, Genie Ontology, and the Genie AI Gateway.

Agentic AI Implementation — Understanding of agentic implementation, agent building, and orchestration, with hands‑on ability to build, validate, and evaluate agents on AWS and Databricks.

AgentBricks & Vector Search — Knowledge of AgentBricks and Databricks Vector Search, or general vector search.

Data Warehouse & Lakehouse — Rich data warehouse and lakehouse experience, plus data modelling fundamentals.

Semantic Foundations — Fundamental knowledge of ontology, knowledge graphs, and semantic layers.

Data Cataloging & Glossary — Knowledge of data cataloging tools and business glossaries.

GOOD-TO-HAVE SKILLS

Cataloging Tools such as Atlan — Familiarity with commercial cataloging platforms, particularly Atlan, is a bonus.

Banking Domain Knowledge — Understanding of banking domains and banking data landscapes.

Banking Assets Domain — Exposure to the banking assets domain, including lending and asset products and their data.

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