Remote AI Data Engineer for Scalable Pipelines (AWS, Spark)

S27a; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Bonuses

Health insurance

401(k) match

Remote-first

Job summary

S27a is seeking a Data Engineer to design and scale data infrastructure powering AI-driven products. You will build distributed pipelines, manage large datasets across cloud environments, and enable experimentation and model development at scale.

The role emphasizes Python/SQL, Spark, and AWS, with collaboration across AI researchers, data scientists, and engineering teams to deliver scalable data solutions and high-quality data platforms.

Qualifications

• Strong Python and SQL skills for data processing.
• Hands-on experience with distributed data processing frameworks.
• Experience with AWS data services and cloud-native architectures.
• Experience with both SQL and NoSQL databases.

Responsibilities

• Design, build, and maintain scalable data pipelines to ingest, process, and transform large-scale datasets from multiple sources.
• Develop and optimize distributed data processing workflows using Spark and cloud-native technologies.
• Build and maintain data storage solutions across SQL and NoSQL systems, ensuring scalability, performance, and reliability.
• Design and implement data architectures on AWS to support high-volume data ingestion, processing, and distribution.
• Write efficient Python and SQL code to extract, transform, validate, and analyze large datasets.
• Ensure data quality, integrity, monitoring, and operational reliability across data pipelines and storage layers.
• Collaborate with AI researchers, data scientists, and engineering teams to support data-intensive applications and experimentation.
• Implement automation, orchestration, and monitoring workflows to support scalable and efficient data operations.

Skills

Python

SQL

AI/ML

Spark

AWS

Job description

S27a is seeking a Data Engineer to design and scale data infrastructure powering AI-driven products. You will build distributed pipelines, manage large datasets across cloud environments, and enable experimentation and model development at scale.

The role emphasizes Python/SQL, Spark, and AWS, with collaboration across AI researchers, data scientists, and engineering teams to deliver scalable data solutions and high-quality data platforms.