Azure Databricks Data Engineer — Scalable Data Platforms

Fractal Analytics; United States; On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Health, dental, vision, life insurance

401(k) Plan

11 paid holidays

12 weeks of Parental Leave

Free time PTO

Job summary

Fractal Analytics is seeking an Azure Databricks Data Engineer to design, develop, and maintain scalable data solutions in the cloud. The role emphasizes Databricks, PySpark, and data pipelines across analytics and AI initiatives.

You will collaborate with stakeholders, architects, and data teams to deliver high-quality platforms, enforce data quality, and support reporting and decision-making in a fast-paced environment.

Qualifications

• Bachelor’s or Master’s degree in CS/IT/Engineering or related field.
• 6-10 years of experience in Data Engineering and Analytics.
• Minimum 3+ years hands-on experience with Azure Databricks.
• Strong experience with PySpark, SQL, and cloud-native data platforms.
• Experience building enterprise-scale data lakes and data warehouses.

Responsibilities

• Design, build, and optimize scalable data pipelines using Azure Databricks.
• Develop ETL/ELT workflows for large-scale datasets.
• Implement batch and real-time data processing with PySpark and Spark SQL.

Skills

PySpark

Spark SQL

Delta Lake

ETL/ELT Pipeline Development

Data Modeling

Data Warehousing Concepts

Data Governance and Data Quality

Agile delivery environments

Python

SQL

Education

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or related field

Tools

Azure Databricks

Azure Data Factory

Azure Data Lake Storage Gen2

Azure Synapse Analytics

Azure Key Vault

Azure Monitor

Azure DevOps

Git

CI/CD Pipelines

Terraform

Job description

Fractal Analytics is seeking an Azure Databricks Data Engineer to design, develop, and maintain scalable data solutions in the cloud. The role emphasizes Databricks, PySpark, and data pipelines across analytics and AI initiatives.

You will collaborate with stakeholders, architects, and data teams to deliver high-quality platforms, enforce data quality, and support reporting and decision-making in a fast-paced environment.