Senior Databricks Data Engineering Lead - Remote

Prabhav Services Inc; United States; Remote; USD 124,000 - 207,000; Part time

Job summary

Prabhav Services Inc. seeks a Senior Forward Deployed Engineer specializing in Databricks to lead end-to-end data engineering implementations in customer environments.

The role combines hands-on engineering, solution architecture, systems integration, and customer-facing leadership. The candidate will translate complex requirements into scalable technical solutions, own implementation, deployment, and delivery outcomes, and collaborate with stakeholders to ensure success across cloud-native data

Qualifications

• 12 years of professional software/data engineering or related roles.
• Strong hands-on Databricks experience for enterprise-scale solutions.
• Expertise in Apache Spark, PySpark, Python, and SQL.

Responsibilities

• Lead end-to-end Databricks implementations, including data engineering and solution architecture.
• Design, build, deploy production-grade data pipelines on Databricks, Spark, PySpark, Python and SQL.
• Build scalable cloud-native data solutions on AWS, Azure, or GCP.
• Design Lakehouse architectures and enterprise data engineering solutions.
• Translate business requirements into technical designs and reusable patterns.
• Integrate Databricks with enterprise systems and data platforms.
• Troubleshoot performance issues and optimize pipelines and Spark workloads.
• Implement CI/CD, automated deployments, and MLOps where applicable.
• Collaborate with customers and cross-functional teams to ensure delivery.

Skills

Databricks

Apache Spark

PySpark

Python

SQL

AWS/Azure/GCP

CI/CD

MLOps

Job description

Prabhav Services Inc. seeks a Senior Forward Deployed Engineer specializing in Databricks to lead end-to-end data engineering implementations in customer environments.

The role combines hands-on engineering, solution architecture, systems integration, and customer-facing leadership. The candidate will translate complex requirements into scalable technical solutions, own implementation, deployment, and delivery outcomes, and collaborate with stakeholders to ensure success across cloud-native data