Realtime Data Engineer for AI-Driven Pricing

Fetcherr; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Fetcherr builds responsible AI and seeks a Data Software Engineer to scale the data infrastructure powering the Large Market Model. You design and maintain real-time data pipelines feeding pricing, inventory, and network optimization, partnering with data scientists and ML engineers to productionize models.

This role blends data engineering with applied AI at scale. You’ll work on scalable, low-latency systems, build robust ETL/ELT processes, and ensure data quality and observability while

Qualifications

• 5+ years of full-time experience in data engineering or similar role.
• Proficient in Python with production-grade coding.
• Strong SQL skills with relational and non-relational stores.
• Experience with cloud infrastructure (GCP BigQuery preferred).
• Familiar with Airflow and Dagster, CI/CD for data pipelines.
• Experience operating high-throughput, low-latency systems in production.
• Excellent collaboration with data science and product teams.

Responsibilities

• Design, build, and maintain scalable, low-latency data pipelines ingesting live market data.
• Develop robust ETL/ELT processes to clean and transform large datasets.
• Architect storage solutions for real-time and batch workloads.
• Partner with data scientists and ML engineers to productionize models.
• Monitor and optimize data systems for reliability and cost efficiency.
• Implement data quality, observability, and governance practices.
• Contribute to evolving data platform architecture as Fetcherr scales.

Skills

Python

SQL

BigQuery

Airflow

Dagster

Cloud infrastructure

ETL/ELT

Data pipelines

CI/CD for data

Production experience

Tools

ClickHouse

Job description

Fetcherr builds responsible AI and seeks a Data Software Engineer to scale the data infrastructure powering the Large Market Model. You design and maintain real-time data pipelines feeding pricing, inventory, and network optimization, partnering with data scientists and ML engineers to productionize models.

This role blends data engineering with applied AI at scale. You’ll work on scalable, low-latency systems, build robust ETL/ELT processes, and ensure data quality and observability while