Open role
Data Engineer
New York City or South Africa·Full-Time
We're looking for a mid-to-senior Data Engineer to build the data systems that power our AI agents and insurance decisioning platform. You'll own end-to-end pipeline design and development, co-build ML model pipelines for propensity and cost forecasting, and architect data integrations with client infrastructure. The ideal candidate brings strong data engineering experience, deep curiosity, and a passion for building in a fast-moving, high-ownership environment. 4-9 years of experience required.
What you’ll do
- Build robust and scalable data pipelines and infrastructure to power intelligent insurance decisioning by marketers and AI agents.
- Own end-to-end design and development of orchestration workflows - from ingesting raw source data to delivering features for modeling and agent interaction.
- Co-design and implement ML model pipelines to forecast, predict, and recommend propensities, costs, and actions relating to insurance acquisition.
- Architect data integrations between client infrastructure and Fount's Data Platform.
- Contribute to technical leadership in data architecture, modeling approach, and agentic workflow discussions.
- Contribute to the development of our actuarial and AI agent toolkits.
What we’re looking for
- 4-9 years of experience in data engineering or data science in financial services or related industries.
- Experience building data pipelines for production software systems.
- Cloud data ecosystems: Amazon S3, Snowflake, Iceberg/Parquet.
- Batch and streaming frameworks: Apache Spark, Kafka, Airflow, dbt.
- Hands-on with file-backed SQL engines like DuckDB or Iceberg; understands partitioning, compaction, and schema evolution.
- Strong data wrangling and feature engineering skills across messy, real-world datasets.
- Familiarity with core risk and finance concepts (retention rates, CLV, loss ratios, underwriting factors).
- Experience building and deploying ML models in production environments.
- Obsessed with AI-first developer tools (Claude Code, Cursor, Codex) to accelerate development while maintaining strong engineering discipline.
Nice to have
- Experience with marketing and digital customer acquisition.
- Exposure to LLM-driven analytics over structured data.
- Familiarity with MLOps practices and tools (MLflow, SageMaker, etc.).
Interview process
- 1.Intro Call - Quick call with a founder to assess mutual fit.
- 2.Technical Assignment and Discussion - Technical assignment presented to candidate to complete, followed by a feedback session led by the candidate on the work produced.
- 3.Co-Work Session - You will work with the Fount team for a few hours on a specified day to assess ways of working compatibility.
- 4.Contracting and Onboarding.