Staff data engineer

Stealth Startup; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

Stealth Startup is seeking a Staff Data Engineer to own and scale its core data platform powering AI-driven consumer marketing products.

You will design scalable, multi-tenant data systems, evolve data models and pipelines, and build infrastructure enabling traditional apps and AI agents to access trusted data. The role requires leading data initiatives and mentoring engineers across the platform.

Qualifications

• 5+ years of data/software engineering experience in data-heavy environments.
• Expert Python and SQL skills.
• Experience with multi-tenant architecture, data modeling, schema evolution.
• Strong knowledge of data warehouses such as Snowflake, BigQuery, or Redshift.
• Experience with AI/LLM data infrastructure is a plus.

Responsibilities

• Design and scale multi-tenant data pipelines and transformation systems.
• Own data models, schemas, contracts, and data quality across the platform.
• Build reliable ingestion, orchestration, monitoring, and data-access systems.
• Work with large-scale consumer datasets across multiple sources.
• Develop infrastructure for AI-agent access, including MCP, vector search, and retrieval systems.
• Drive architecture decisions and mentor engineers across the data platform.

Skills

Python

SQL

Data modelling

Data pipelines

Cross-functional collaboration

Tools

dbt

SQLMesh

Airflow

Snowflake

BigQuery

Redshift

Job description

We are looking for a Staff Data Engineer to own and scale the core data platform powering its AI-driven consumer marketing products. You’ll design scalable, multi-tenant data systems, evolve data models and pipelines, and build infrastructure that enables both traditional applications and AI agents to access trusted data.

Responsibilities

• Design and scale multi-tenant data pipelines and transformation systems.
• Own data models, schemas, contracts, and data quality across the platform.
• Build reliable ingestion, orchestration, monitoring, and data-access systems.
• Work with large-scale consumer datasets across multiple sources.
• Develop infrastructure for AI-agent access, including MCP, vector search, and retrieval systems.
• Drive architecture decisions and mentor engineers across the data platform.

Requirements

• 5+ years of data/software engineering experience in data-heavy environments.
• Expert Python and SQL skills.
• Strong experience with dbt, SQLMesh, Airflow, or similar tools.
• Deep knowledge of Snowflake, BigQuery, Redshift, or similar data warehouses.
• Experience with multi-tenant architecture, data modeling, schema evolution, and production data platforms.
• Strong ownership and ability to lead ambiguous, cross-functional technical initiatives.
• Experience with AI/LLM data infrastructure is a plus.