Data Engineer – AI Data Pipelines on AWS (Remote)

TalentHop; United States; Remote; USD 110,000 - 160,000; Full time

Benefits offered by this job

Equity compensation

Remote-first environment

Health insurance reimbursement

401(k) plan with company match

Job summary

TalentHop seeks a DATA ENGINEER to scale data infrastructure for AI research and product development. You will build distributed pipelines, manage storage across SQL/NoSQL, and ensure reliable data systems for experimentation at scale.

You will collaborate with AI researchers and engineers, optimize cloud-native workflows, and implement automation and monitoring to support data-intensive applications across a remote-first organization.

Qualifications

• Proficiency in Python and SQL with strong programming skills.
• Experience with distributed data processing frameworks and big data environments.
• Understanding of scalable data architectures and data modeling.

Responsibilities

• Design, build, and maintain scalable data pipelines for large 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 and performance.
• Design and implement data architectures on AWS for high-volume data ingestion and processing.
• Write efficient Python and SQL code for data extraction, transformation, validation, and analysis.
• Ensure data quality, integrity, and operational reliability across pipelines and storage layers.
• Collaborate with AI researchers, data scientists, and engineering teams to support experimentation.
• Implement automation, orchestration, and monitoring workflows for scalable data operations.

Skills

Python

SQL

Spark

Distributed data processing

Data architectures

Tools

Apache Spark

AWS

SQL databases

NoSQL databases

Job description

TalentHop seeks a DATA ENGINEER to scale data infrastructure for AI research and product development. You will build distributed pipelines, manage storage across SQL/NoSQL, and ensure reliable data systems for experimentation at scale.

You will collaborate with AI researchers and engineers, optimize cloud-native workflows, and implement automation and monitoring to support data-intensive applications across a remote-first organization.