Remote Databricks Engineer: Data Lakehouse & MLflow

BairesDev; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote work: 100% from anywhere

Flexible hours

Home setup provided

Paid parental leaves and holidays

Job summary

BairesDev is seeking a Databricks Engineer to design and maintain scalable data pipelines on the Databricks Lakehouse platform. You will bridge raw data and insights, ensuring high performance, governance, and reliability across the data lifecycle.

You will collaborate with data scientists and analysts to deliver a high-performance analytics platform, while optimizing clusters and jobs for cost efficiency and scalability in a 100% remote, globally distributed team.

Qualifications

• 4+ years of experience in Data Engineering, Software Engineering, or Database Administration.
• Proven ability to build data pipelines and analytics on the Databricks Lakehouse platform.
• Experience managing notebooks, jobs, and Unity Catalog governance.
• Hands-on experience with Delta Lake and MLflow for data processing and lifecycle management.

Responsibilities

• Design and implement scalable data pipelines using Databricks notebooks and automated jobs.
• Build and optimize data lakehouse architectures leveraging Delta Lake for ACID transactions and reliability.
• Manage data governance and security frameworks using Unity Catalog to ensure compliant data access.
• Develop and maintain machine learning lifecycles and experiment tracking using MLflow.
• Collaborate with data scientists and analysts to provide a high-performance platform for advanced analytics.
• Optimize cluster configurations and job execution to ensure cost-efficiency and system performance.

Skills

Data engineering

Pipelines design

Cloud data platforms

English proficiency

Tools

Databricks Lakehouse

Delta Lake

MLflow

Unity Catalog

Job description

BairesDev is seeking a Databricks Engineer to design and maintain scalable data pipelines on the Databricks Lakehouse platform. You will bridge raw data and insights, ensuring high performance, governance, and reliability across the data lifecycle.

You will collaborate with data scientists and analysts to deliver a high-performance analytics platform, while optimizing clusters and jobs for cost efficiency and scalability in a 100% remote, globally distributed team.