Syren Cloud Inc
Databricks Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Databricks Engineer with a focus on ML, based in Atlanta, GA. Contract length is unspecified, with a senior-level pay rate. Key skills include Databricks, Spark, Airflow, and ML infrastructure experience (6-8+ years required).
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
440
-
🗓️ - Date
April 14, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Atlanta, GA
-
🧠 - Skills detailed
#AI (Artificial Intelligence) #Leadership #Data Engineering #ML (Machine Learning) #Databricks #Data Science #Spark (Apache Spark) #Scala #Airflow #Data Pipeline
Role description
Hi,
Please find below the job description.
Role: Databricks Engineer - ML Focused
Location: Atlanta, GA
Client: Floor & Decor
Must-Have Skills:
• Strong proficiency in the Databricks toolchain, specifically Spark and Airflow.
• Hands-on experience with Feature Stores and Data Versioning within an ML lifecycle.
• Proven ability to be a technical leader on a small, high-impact team.
• Exceptional communication skills and the ability to work independently.
Experience in Years: Senior-level (typically 6-8+ years in Data Engineering, with at least 2-3 years focused on ML infrastructure).
Preferably Atlanta-based for long-term collaboration; however, open to highly qualified remote talent if they demonstrate strong leadership and self-sufficiency.
Responsibilities:
• Design and maintain scalable data pipelines using Spark and Airflow.
• Build and manage Feature Stores to support Data Science use cases.
• Implement data versioning to ensure reproducibility of ML models.
• Serve as a technical lead, bridge the gap between raw data and model-ready features, and work closely with Data Scientists on AI use cases.
Hi,
Please find below the job description.
Role: Databricks Engineer - ML Focused
Location: Atlanta, GA
Client: Floor & Decor
Must-Have Skills:
• Strong proficiency in the Databricks toolchain, specifically Spark and Airflow.
• Hands-on experience with Feature Stores and Data Versioning within an ML lifecycle.
• Proven ability to be a technical leader on a small, high-impact team.
• Exceptional communication skills and the ability to work independently.
Experience in Years: Senior-level (typically 6-8+ years in Data Engineering, with at least 2-3 years focused on ML infrastructure).
Preferably Atlanta-based for long-term collaboration; however, open to highly qualified remote talent if they demonstrate strong leadership and self-sufficiency.
Responsibilities:
• Design and maintain scalable data pipelines using Spark and Airflow.
• Build and manage Feature Stores to support Data Science use cases.
• Implement data versioning to ensure reproducibility of ML models.
• Serve as a technical lead, bridge the gap between raw data and model-ready features, and work closely with Data Scientists on AI use cases.
