Data Engineer

FountAI, Inc.; New York (NY); On-site; USD 100,000 - 140,000; Full time

Job summary

FountAI, Inc. is seeking a mid-to-senior Data Engineer to develop data systems that drive AI agents and insurance decision-making. In this role, you will own pipeline design, contribute to ML model pipelines, and integrate client infrastructure with Fount's Data Platform. Candidates should have 4-9 years of experience in data engineering, knowledge of building scalable data pipelines, and familiarity with tools like Apache Spark and Kafka. Join us if you are passionate about a fast-paced, innovative environment!

Qualifications

• 4-9 years of experience in data engineering or data science in financial services.
• Experience building data pipelines for production software systems.
• Strong data wrangling and feature engineering skills.

Responsibilities

• Build robust and scalable data pipelines for insurance decisioning.
• Design and develop orchestration workflows from raw data to modeling.
• Implement ML model pipelines for cost and propensity forecasting.

Skills

Data pipeline building

Data wrangling

Feature engineering

Apache Spark

Kafka

Airflow

Machine learning model deployment

Tools

DuckDB

Iceberg

MLflow

SageMaker

dbt

Job description

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.
• 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.).