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Dscout

AI Data Engineer

RemoteUnited States only
Published
Role
Data Engineering
Experience
Senior
Salary not disclosed
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Open to US only. Set where you work from to check your eligibility.

No BS summary

Data engineer with 5+ years, strong Python, production ML/AI systems exposure, and real ownership of data pipelines. Must be US-remote eligible, excluding Montana, Hawaii, Alaska, and Washington DC. Snowflake/Postgres, orchestration tools, and GCP or AWS are core to the role.

Core skills

PythonData pipelinesML systems

Required skills

SnowflakePostgreSQLAirflow/DagsterGCP/AWS

Optional skills

dbtLLM evaluationLLM observabilityMCPAgentic data workflows

What you'll do

  • Design, build, and own the data pipelines that move and transform data from our application and third-party sources into relational databases - keeping them reliable and well-modeled as volume and complexity grow
  • Partner with analytics engineering to build the data models and reporting that give researchers and teams real visibility into how their work is performing
  • Own data quality as a first-class concern across ingestion, modeling, and reporting. Catch problems before they reach a model, a dashboard, or a user, and fix them
  • Build and ship production AI systems the data infrastructure and services that ML features run on
  • Design and own evaluation systems that tell us whether an AI feature is ready to ship and holding up over time: eval harnesses, test datasets, and production monitoring built as software, not one-off analyses
  • Set the standard for how data work gets done. Write clearly, share context early, and make the people around you faster

What they require

  • 5+ years of experience in data engineering, with meaningful exposure to ML systems in production
  • Deep data engineering experience: you've personally built and owned pipelines that move data from application sources into a warehouse at scale, and you know what breaks, when, and why
  • Strong Python skills and fluency across the data stack (we use Snowflake and Postgres)
  • Experience with orchestration tools like Airflow, Dagster, or similar
  • Experience working with cloud computing environments like GCP or AWS.
  • A track record of working closely with analytics engineers or data analysts to build reliable, well-documented data models
  • Hands-on experience shipping AI or ML systems that real users depended on in production, and owning what happened after launch
  • A genuine point of view on evaluation: you treat evals as something you build, not a report you write
  • A high-agency mindset. You can take an ambiguous problem and drive it to a working outcome without a fully-scoped ticket
  • Fluency across the data lifecycle, from production-facing features to the internal analytics that drive decision-making
  • Comfort working across the data lifecycle, from production-facing features to the internal analytics that drive decision-making
  • Comfort using AI coding tools (Cursor, Claude Code, Copilot, or similar) as a real part of your workflow
  • Preferred: Experience with dbt or similar data modeling frameworks
  • Preferred: Familiarity with LLM evaluation and observability tooling
  • Preferred: Exposure to MCP-based tooling or agentic data workflows

Benefits

  • A strong and competitive compensation package with a built-in bonus and equity program.
  • An incredible and progressive benefits package (for both you and your dependents) to support work/life balance, including flexible PTO, 15 company holidays, 12 weeks of paid parental leave, 401k match, and much more.
  • An education stipend to support your growth & development, and a remote work stipend.
  • A company that is open and transparent with our team. You will know what is happening and why it matters.

Dscout is building a UX research platform trusted by major brands; its tools help teams understand the humans behind their products.

UX Research

Details

Apply routeGreenhouse
Salary not disclosed