Enterprise AI Analytics Engineer — Forward-Deployed

Golden Analytics, Inc.; New York (NY); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive salary

Equity

Job summary

Golden Analytics, Inc. is seeking a forward-deployed analytics engineer to own the technical win across enterprise deals. You’ll run discovery demos, build proofs of concept against real customer data in Snowflake, Databricks, BigQuery, and dbt-modeled environments, and address governance and architecture questions.

You will embed in deployments, model real data, and drive genuine adoption while also sharing practical learnings with the data community through talks, posts, and tutorials.

Qualifications

• Senior-level experience in solutions engineering, sales engineering, analytics engineering, or a technical field role where you owned the technical win.
• Fluency with cloud data warehouses (Snowflake, Databricks, BigQuery) and the modern data stack (dbt, semantic layers, analytics engineering workflow).
• Strong SQL and understanding of how analytics gets built, governed, and used in a real company.
• Visible instinct to teach and share, with a desire to build a public voice under your own name.
• Comfort with pre-GA ambiguity and building a function from scratch.

Responsibilities

• Own the technical win end to end, from discovery demos to proofs of concept against real customer data.
• Embed in enterprise deployments, model customer data, and drive adoption in the environment.
• Create content that teaches and shows practical analytics to the market, including talks, videos, and how-tos.
• Collaborate with product and engineering to ensure feedback flows back and the roadmap aligns with field needs.

Skills

Solutions engineering

Sales engineering

Analytics engineering

Public speaking

Tools

Snowflake

Databricks

BigQuery

dbt

Semantic layers

Job description

Golden Analytics, Inc. is seeking a forward-deployed analytics engineer to own the technical win across enterprise deals. You’ll run discovery demos, build proofs of concept against real customer data in Snowflake, Databricks, BigQuery, and dbt-modeled environments, and address governance and architecture questions.

You will embed in deployments, model real data, and drive genuine adoption while also sharing practical learnings with the data community through talks, posts, and tutorials.