Azure Databricks Data Engineer | Lakehouse & ETL Expert

• We are seeking a skilled Databricks Engineer with strong experience in Azure Databricks and Python (PySpark) to design, build, and optimize scalable data processing pipelines.
• The ideal candidate will work closely with data engineers, analysts, and stakeholders to deliver high-performance data solutions on the Azure cloud platform.

Key Responsibilities

• Design, build, and maintain data pipelines and ETL processes using Databricks and Apache Spark.
• Optimize data workflows for performance, scalability, and cost efficiency.
• Implement data Lakehouse architecture and manage data ingestion from multiple sources.
• Collaborate with data scientists and analysts to enable advanced analytics and machine learning workloads.
• Ensure data quality, governance, and security across all data assets.
• Monitor and troubleshoot Databricks clusters, jobs, and workflows.
• Integrate Databricks with cloud services (AWS, Azure, or GCP) and other enterprise systems.
• Document processes, standards, and best practices for data engineering.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering or big data technologies.
• Hands-on experience with Databricks, Apache Spark, and PySpark.
• Strong knowledge of SQL, Python, and data modeling principles.
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services.
• Familiarity with Delta Lake, Lakehouse architecture, and data governance.
• Understanding of CI/CD pipelines and DevOps practices for data workflows.
• Excellent problem-solving and communication skills.

Nice to Have

• Experience with Delta Lake and Lakehouse architecture.
• Knowledge of Azure Data Factory (ADF) for orchestration.
• Experience with SQL and Spark SQL.
• Azure certifications related to data engineering.