AI Data Engineer

Role overview Join an AI-first engineering studio as a hands-on builder who shapes the data foundation for a US-based startup partner. The role goes beyond maintaining pipelines: it involves designing trustworthy data models in Snowflake, integrating scattered sources, and partnering directly with product and business leaders to turn questions into outcomes.

Responsibilities - Design, build, and own ETL/ELT pipelines that pull data from APIs, SaaS tools, CRMs, and transactional databases into Snowflake. - Model data inside Snowflake so it is clean, trustworthy, and ready for analytics and product use cases. - Build and maintain integrations across the stack, choosing between off-the-shelf connectors and custom code as appropriate. - Work directly with product and business leaders to translate ambiguous questions into concrete data solutions. - Use AI tools and agents to accelerate personal workflows and automate manual processes for the team. - Take end-to-end ownership: spot the problem, propose the solution, ship it, and iterate.

Requirements - Hands-on data engineering experience with production pipelines written in real Python and SQL code. - Strong Snowflake expertise, including data modeling, performance tuning, and cost awareness. - Experience integrating multiple data sources and orchestrating pipelines with tools like Airflow, dbt, Fivetran, or Airbyte. - Practical experience building AI agents or LLM-powered workflows on top of company data. - Business and product sense, with the ability to engage non-technical stakeholders and prioritize by impact. - Impeccable spoken and written English, with daily collaboration alongside a US team. - Comfort operating in an early-stage, ambiguous environment as a builder rather than a ticket-taker.

Nice to have - Startup or founder/co-founder background. - Familiarity with CI/CD, testing, and version control practices for data, including Git, dbt tests, and data quality checks. - Cloud experience with AWS, GCP, or Azure.

Benefits and work setup - Remote within LATAM, full-time engagement.