Senior Analytics Engineer — Build AI-Driven Data Platform

Hercules; San Francisco (CA); On-site; USD 100,000 - 250,000; Full time

Benefits offered by this job

Unlimited AI token budget

Take what you need vacation policy

Healthcare, vision, and dental

Daily lunches, dinners and snacks in a

Job summary

Hercules in San Francisco is seeking a senior analytics and full-stack engineer to own our data stack and help shape the future of AI software development. You will manage ETL, data modeling, semantic layers, and BI dashboards used across the company.

We expect strong experience with DBT, BigQuery, Omni and Looker-like tools, plus system design and a drive for fast, self-serve data. The team prefers in-office work but will consider exceptional remote candidates in US time zones who can travel to

Qualifications

• Strong software fundamentals in system design, architecture, data modeling, and API design.
• Write clean, maintainable code and work effectively in monorepos.
• Strong data modeling experience with DBT or similar declarative framework.
• Experience with semantic layers using Omni, Looker, or similar.
• Strong BI understanding and data visualization.
• AI fluency to accelerate workflows.

Responsibilities

• Own the full data stack from ETL to BI dashboards.
• Move data from providers into the Data Warehouse (BigQuery).
• Model and clean data with DBT and medallion architecture.
• Define and model key business metrics with semantic layers.
• Create dashboards and visualizations to enable self-serve insights.

Skills

System design

Architecture

Data modeling

API design

Code quality

Monorepos

Tools

DBT

Omni

Looker

Airbyte

BigQuery

Clickhouse

Job description

Hercules in San Francisco is seeking a senior analytics and full-stack engineer to own our data stack and help shape the future of AI software development. You will manage ETL, data modeling, semantic layers, and BI dashboards used across the company.

We expect strong experience with DBT, BigQuery, Omni and Looker-like tools, plus system design and a drive for fast, self-serve data. The team prefers in-office work but will consider exceptional remote candidates in US time zones who can travel to