Analytics Engineer: Data Pipelines & AI Agents (Hybrid, Equity)

Thesiscareers; New York (NY); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Equity

Job summary

Thesis is seeking an Analytics Engineer in New York, NY, offering a hybrid role with a $120,000–$150,000 base plus equity. The role focuses on building robust data infrastructure, reliable ETL pipelines, and AI-driven products for a fast-growing nootropics company.

You will own data pipelines, BI reporting, and the development of AI-enabled workflows, collaborating with a small, impact-focused team and a Director of Data Analytics.

Qualifications

• Strong SQL. Real warehouse queries, not notebooks.
• Hands-on with data pipelines and ETL, keeping them running.
• Experience with a BI tool such as Metabase, Looker, or Tableau.
• Hands-on experience building with LLMs: prompting, retrieval, tool use, agentic patterns.
• Solid fundamentals in databases and APIs.
• Ability to move from ambiguous business questions to a prototype to production.
• Strong product instincts and knowing where AI adds real value.
• Comfort with ambiguity and ownership over tickets.

Responsibilities

• Own the data foundation: maintain ETL pipelines feeding Snowflake and BI layers.
• Be the internal data resource: turn ad hoc questions into SQL, models, and answers.
• Build AI into how the company works: design AI agents and workflows, integrate LLMs, and enable self‑service.

Skills

Strong SQL

ETL pipelines

BI tooling

LLM prompting

Databases & APIs

Ambiguity tolerance

Tools

Snowflake

Metabase

Looker/Tableau

APIs

Job description

Thesis is seeking an Analytics Engineer in New York, NY, offering a hybrid role with a $120,000–$150,000 base plus equity. The role focuses on building robust data infrastructure, reliable ETL pipelines, and AI-driven products for a fast-growing nootropics company.

You will own data pipelines, BI reporting, and the development of AI-enabled workflows, collaborating with a small, impact-focused team and a Director of Data Analytics.