Databricks Data Engineer

Introduction

As a Databricks Data Engineer, you will be responsible for designing, developing, and maintaining scalable data engineering solutions using the Databricks Lakehouse Platform.

You will work with Apache Spark, Delta Lake, and cloud technologies to build and optimize ETL/ELT pipelines, define data architecture, and provide technical leadership in implementing best practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Delta Lake.
• Build and optimize batch and streaming ETL/ELT workflows for enterprise data platforms.
• Gather business requirements and translate them into efficient data engineering solutions.
• Monitor, troubleshoot, and resolve production issues while ensuring data quality and platform reliability.
• Collaborate with cross-functional teams to deliver secure, high-performance cloud data solutions.
• Maintain Databricks workspaces, clusters, jobs, and data governance following industry best practices.
• Mentor team members and stay current with emerging data engineering and cloud technologies.

Education

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related field.

Experience

• 4+ years of experience in Data Engineering.
• Hands-on experience with Databricks, Apache Spark (PySpark/Spark SQL), and Delta Lake.
• Strong experience developing ETL/ELT pipelines and working with data lakes or Lakehouse architectures.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Proficiency in Python and SQL.
• Experience with orchestration tools such as Azure Data Factory, Airflow, or similar is preferred.
• Strong analytical, problem-solving, communication, and collaboration skills.