Senior Data Engineer (Remote) - ML in Production Pipelines

FLOAT; United States; Remote; USD 149,000 - 201,000; Full time

Job summary

FLOAT is seeking a Senior Data Engineer for its remote Engineering team. You will build and own production-grade data pipelines and ML-ready workloads that power Float's Intelligence features.

This role involves ownership of data pipelines, contributing to AI features in production, and shaping an event-driven architecture with Kafka/Debezium. You will collaborate asynchronously with a global team, ensuring reliability, documentation, and scalable data infrastructure as the company moves toward

Qualifications

• Applied ML/AI in production: shipped an ML/AI feature used by customers.
• Pipeline ownership and debugging: owned pipelines and resolved issues with lineage/logs/data samples.
• Feature delivery: data work feeds customer-facing features, not just internal tooling.
• TypeScript/Node.js: production-level TS codebases with strong typing.
• SQL and databases: complex analytical SQL with attention to warehouse cost/performance.
• Software engineering practices: design-before-code, tests, code reviews, AI-assisted coding tools.

Responsibilities

• Intelligence pipeline ownership: end-to-end ownership of data pipelines powering features.
• Applied ML in production: contribute to AI features in production, build reliable data infra.
• Pipeline health and maintenance: ensure pipelines and data infra are reliable and well-documented.

Skills

TypeScript/Node.js

SQL and databases

Applied ML/AI in prod

Pipeline ownership

Documentation

Timefold/OR-Tools

Tools

dbt

BigQuery

Snowflake

Kafka

Debezium

Job description

FLOAT is seeking a Senior Data Engineer for its remote Engineering team. You will build and own production-grade data pipelines and ML-ready workloads that power Float's Intelligence features.

This role involves ownership of data pipelines, contributing to AI features in production, and shaping an event-driven architecture with Kafka/Debezium. You will collaborate asynchronously with a global team, ensuring reliability, documentation, and scalable data infrastructure as the company moves toward