Remote Data Engineer: Spark, Databricks & Snowflake

Quality Ai; Northern (KY); Hybrid; USD 110,000 - 120,000; Full time

Benefits offered by this job

401k plan

Healthcare benefits

Flexible and casual culture

Job summary

QualityAI is seeking a Data Engineer to join our growing team in the United States. This role focuses on building end-to-end data pipelines and leveraging cloud platforms such as Databricks and Snowflake to enable scalable data processing.

You will work closely with analytics and engineering teams to design reliable data solutions, optimize Spark performance, and implement automation and IaC practices to drive efficiency and cost savings.

Qualifications

• Hands-on Python and PySpark with a solid understanding of Spark concepts, performance tuning, and scalable data processing.

Responsibilities

• Strong hands-on experience in Python and PySpark, with a solid understanding of Spark concepts, performance tuning, and scalable data processing.
• Experience working with modern data management platforms such as Snowflake, Databricks, or similar cloud-based data platforms.
• Good understanding of data pipeline design, development, orchestration, and monitoring, including batch and streaming data processing.
• Familiarity with Medallion Architecture concepts, including bronze, silver, and gold layer design and best practices for data transformation.
• Strong understanding of autoscaling, cluster optimization, and cost-efficient data processing in cloud or distributed data environments.
• Experience with CI/CD, DevOps practices, and version control, with preference for candidates who have exposure to Terraform or infrastructure-as-code tools.
• Ability to collaborate with business, analytics, and engineering teams to design reliable, reusable, and scalable data solutions.

Skills

End-to-end data pipelines

Databricks

Snowflake

PySpark

Python

Cloud data platforms

Tools

Terraform

CI/CD tools

Job description

QualityAI is seeking a Data Engineer to join our growing team in the United States. This role focuses on building end-to-end data pipelines and leveraging cloud platforms such as Databricks and Snowflake to enable scalable data processing.

You will work closely with analytics and engineering teams to design reliable data solutions, optimize Spark performance, and implement automation and IaC practices to drive efficiency and cost savings.