Data engineer of agentic systems

When you join the Fountain team, you become part of the leading enterprise solution for frontline workforce management. Fountain’s automated, customizable platform provides a seamless applicant experience for workers, while ensuring organizations can scale and manage their frontline talent. We’ve helped hundreds of companies like UPS, CLEAR, Stitch Fix, GoPuff, Fetch, and sweetgreen to hire, onboard, and manage over 14 million workers in more than 75 countries.

• Design and build the agentic development workflow for the data team.
• Agent-authored models and pipeline changes, the context and tooling those agents operate through, PR and review patterns, CI that catches what agents get wrong, the guardrails that make it safe to run against production, and the standards that make any of it repeatable across a team.
• Push that reach upstream into the product.
• Build the context and tooling that shape how features get conceived and built in the first place, and verify data architecture while changes are in development.
• Build the evaluation layer.
• Regression suites, correctness checks, lineage awareness, and observability on the agents themselves.
• Build agentic analytics capability for the company.
• Semantic context, skills, MCP surfaces, access controls, and query and cost guardrails that let non-technical teams get answers they can act on, along with the honest scoping of what the system won’t answer.
• Drive adoption.
• Work alongside the engineers on the data team and stakeholders across GTM, Finance, Product, and Support, teaching the patterns, watching where people get stuck, and closing the gap between what you built and how people actually work.
• Stay hands-on in the platform.
• You won’t own the models and pipelines, but you’ll work in that codebase constantly, and you should be able to fix what you find.

• 5+ years in data engineering, analytics engineering, or a closely related role, or equivalent depth arrived at another way. What you’ve built and operated matters more to us than the number.
• Real depth in analytical data modeling and SQL.
• You can read a normalized transactional schema, design something that answers business questions without falling over, and spot when a generated model is subtly wrong.
• Hands-on production experience with dbt and an orchestrator.
• Dagster is what we run; Airflow, Prefect, or Temporal transfers fine. You should know the operational reality of a large DAG, not just the syntax.
• Strong Python and the software engineering habits that go with it: version control, testing, code review, CI/CD.
• You have shipped agentic or LLM-powered systems to production.
• Tool and function calling, context and retrieval design, orchestrating multi-step workflows, and evaluating all of it. You should be able to walk through something you built, how you measured whether it worked, and where it failed. This is the requirement we care most about.
• Sound judgment about data governance and PII in a multi-tenant environment. We handle applicant and worker data across 75+ countries, and exposing it through an LLM surface raises the stakes on getting access boundaries right.
• You can bring people with you.
• This role changes how the data team, product engineers, and other departments do their work. That requires listening well, teaching patiently, and being persuasive without a title that makes anyone do anything.
• Будет плюсом: Depth in a columnar or MPP warehouse, especially ClickHouse Cloud and ClickPipes; Snowflake, BigQuery, or Redshift also translates; Building with Claude: the API, Claude Code, the Agent SDK, MCP servers, or subagent patterns; AWS, Kubernetes, and infrastructure as code, enough to debug your own deployment; Semantic layer and BI tooling (Omni, Looker, dbt Semantic Layer, Cube); LLM observability and evaluation tooling (Langfuse, Braintrust, or equivalent); Streaming and CDC internals (Debezium, Kafka, Kinesis); Having led a technical practice change on a team that was skeptical at the start; HR tech, high-volume hiring, workforce management, or another domain with heavy operational data

• We employ a diverse team all over the world. Each Fountaineer is given the freedom to do their best work from wherever they choose.
• We also understand the importance of in-person connections and hold in-person meetings with your team and meet annually as an organization to build our relationships and focus on the future of moving Fountain Forward.
• The benefits we offer in the United States include competitive health plans and a retirement plan.
• Some Fountain-wide perks offered to all employees across the globe include a flexible vacation policy, paid holidays, monthly lunch stipends, annual allowances for ongoing education related to your profession and career advancement, along with home office, cell phone, and wellness reimbursements.
• Fountain is a global employer, so some benefit offerings will vary from country to country.