
USA_Senior Data Scientist
Varite · Atlanta, GA
Strong hiring record · median 6 days open
Hiring signal
Actively hiring
Posted 7 days ago · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted 7 days ago
- Still listed on the employer's own board
- Publishes a salary range
Pay Rate Range
$ 49.24 - 51.51/hr.
Role
Senior Databricks AI Engineer
Job Description
We are seeking a highly skilled Senior Databricks AI Engineer to design, develop, and deploy scalable data and AI solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in Data Engineering, Machine Learning, Generative AI, and cloud technologies, with hands-on experience building enterprise-grade AI applications and data platforms.
Key Responsibilities
Data Engineering
- Design and develop scalable data pipelines using Databricks, PySpark, Delta Lake, and Spark SQL.
- Build ELT/ETL solutions for structured and unstructured data.
- Implement Medallion Architecture (Bronze, Silver, Gold layers).
- Optimize Databricks jobs, clusters, and workflows for performance and cost efficiency.
- Manage data ingestion from multiple cloud and on-premise sources.
AI & Machine Learning
- Develop and deploy Machine Learning models using Databricks ML and Python.
- Implement MLOps practices for model training, deployment, monitoring, and governance.
- Build predictive analytics solutions and recommendation engines.
- Create feature stores and reusable ML pipelines.
Generative AI
Design and develop GenAI applications using
o Large Language Models (LLMs)
o Retrieval Augmented Generation (RAG)
o Vector Databases
o AI Agents and Multi-Agent Frameworks
Design and develop scalable data pipelines using Databricks.
Implement machine learning models and MLOps practices.
Optimize workflows for performance and cost efficiency.
Collaborate with stakeholders to deliver AI-driven solutions.
Develop generative AI applications and integrate various AI technologies.
Essential Skills
Experience in healthcare or banking domains is beneficial.
Familiarity with AI governance and agentic AI is a plus.
Knowledge of MLOps practices is advantageous.
Understanding of data modernization programs is helpful.
Certification in Databricks or machine learning is preferred.
Strong expertise in Databricks and data engineering is essential.
Proficiency in machine learning and AI model deployment is critical.
Experience with cloud platforms like Azure or AWS is necessary.
Familiarity with data pipeline design and optimization is required.
Knowledge of generative AI technologies is a must.
Skills
Digital
Machine Learning~Digital
Cloud Foundry~Digital
Databricks~Digital
PySpark~Generative AI
Experience Required
4-6 years
Skills
Category
Name
Required
Importance
Experience
SkillCategoryTest1_MN
Databricks
Yes
1
>7 years
SkillCategoryTest1_MN
Digital
Cloud Foundry
Yes
1
>7 years
SkillCategoryTest1_MN
Digital
Machine Learning
Yes
1
>7 years
SkillCategoryTest1_MN
Digital
PySpark
Yes
1
>7 years
SkillCategoryTest1_MN
Generative AI
Yes
1
>7 years
Skills
- Databricks
- Machine Learning
- Generative AI
- PySpark
- Delta Lake
- Spark
- SQL
- ELT
- ETL
- Python
- MLOps
- LLM
- Retrieval-Augmented Generation
- Vector Databases
- Azure
- AWS
- Foundry
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