Remote Data Engineer - Cloud Pipelines & AI Systems

Expert Technical Solutions; EE. UU.; A distancia; USD 110.000 - 150.000; Jornada completa

Descripción de la vacante

Expert Technical Solutions seeks a Data Engineer for an immediate 6-month contract with a strong possibility of extension to permanent. The role is fully remote from home in the United States.

You will design, build, and operate intelligent data pipelines and infrastructure to power ML and AI-driven product capabilities. This position spans data engineering, applied AI, and production-grade ML engineering, collaborating with Product, BI, and Data teams to establish standards and deliver

Formación

• 3–5 years of data engineering experience, preferably on AWS cloud data platforms.
• Hands-on experience building, maintaining, and supporting cloud-based data pipelines.
• Strong knowledge of PySpark, Databricks, and SQL.
• Proficient in Python and data modeling, data warehousing, and analytics concepts.
• Experience with CI/CD practices, automated deployment, and unit testing.

Responsabilidades

• Design, build, and maintain scalable cloud-based data pipelines and data infrastructure.
• Deliver high-quality data models and curated datasets for analytics and reporting.
• Optimize Spark, PySpark, and SQL workloads for performance and cost efficiency.
• Support production data pipelines via monitoring and incident resolution.
• Document data flows, pipeline logic, and operational processes.

Conocimientos

PySpark

SQL

Python

Data modeling

Data warehousing

ETL/ELT

CI/CD

AWS cloud

Databricks

Spark

Troubleshooting

Herramientas

Databricks

AWS

Spark

Kafka

Kinesis

Descripción del empleo

Expert Technical Solutions seeks a Data Engineer for an immediate 6-month contract with a strong possibility of extension to permanent. The role is fully remote from home in the United States.

You will design, build, and operate intelligent data pipelines and infrastructure to power ML and AI-driven product capabilities. This position spans data engineering, applied AI, and production-grade ML engineering, collaborating with Product, BI, and Data teams to establish standards and deliver