Databricks Engineer

We need to provide quality profiles to the client. When looking for experience in Databricks on Google Cloud Platform (GCP), you need a blend of core Databricks skills, GCP-specific cloud expertise, and native integration knowledge.

There are vast differences between Azure and GCP. We need to have profiles who have worked on GCP and Databricks as Client is mainly focusing on GCP.

Job Title – Databricks Engineer

Location – Phoenix, AZ – Hybrid 3 days a week.

Databricks Engineer

Role Overview

We are seeking a highly skilled Databricks Engineer to lead the design, implementation, and optimization of scalable cloud-based data platforms. This role requires deep expertise in Lakehouse architecture, Databricks, Apache Spark, and Delta Lake, along with proven experience delivering end-to-end enterprise data engineering solutions.

Key Responsibilities

• Design and deliver end-to-end data engineering pipelines, including batch and real-time streaming solutions.
• Lead implementation of:
• Cloud-based data lakehouse platforms integrating diverse data sources.
• Real-time data processing pipelines for operational and analytical use cases.
• Develop scalable ETL/ELT pipelines using PySpark, Scala, and SQL.
• Implement advanced data modeling solutions including 3NF, dimensional modeling, and enterprise data warehousing strategies.
• Design and build incremental data loading frameworks and metadata-driven ingestion pipelines.
• Establish data quality frameworks and governance standards.
• Implement and manage Unity Catalog, including fine-grained security and access controls.
• Leverage Databricks components such as:
• Delta Live Tables
• Autoloader
• Structured Streaming
• Databricks Workflows
• Integration with orchestration tools (e.g., Apache Airflow)
• Drive CI/CD automation, deployment strategies, and DevOps best practices.
• Optimize performance of pipelines, Spark jobs, and compute resources.
• Provide architectural guidance and technical leadership across cross-functional teams.
• Engage with stakeholders and clients to translate business requirements into scalable technical solutions.

Deep expertise in:

• Databricks and cloud-native storage/compute platforms
• Apache Spark (batch & streaming)
• Delta Lake & Lakehouse architecture
• Distributed data processing systems
• Strong hands-on programming skills in Python, PySpark, Scala, and SQL.