Senior Data Engineer – Databricks - 1613

Must Have:

• Databricks and Snowflake for data platforms
  
• Spark or PySpark with Python for batch processing
  
• Advanced SQL with query tuning, partitioning, clustering
  
• Data modeling using star, snowflake, SCD, OBT, normalized models
  
• Experience with Medallion architecture
  
• Data ingestion pipelines and large-scale migrations
  
• Orchestration tools for data workflows
  
• Data platform debugging and observability
  

Responsibilities:

• Design and build large-scale data pipelines for ingestion and transformation
  
• Develop ETL and ELT frameworks using Databricks and Spark
  
• Optimize SQL queries and improve data performance
  
• Build and maintain scalable data models across lakehouse platforms
  
• Lead data migration efforts across systems and environments
  
• Implement orchestration for reliable data workflows
  
• Monitor data pipelines and resolve production issues
  
• Ensure governance, data quality, and observability across platforms
  

Qualifications:

• 7+ years in data engineering or data platform roles
  
• Strong hands-on experience with Databricks or Snowflake
  
• Deep expertise in SQL and distributed data processing
  
• Experience building scalable data models and architectures
  
• Proven experience with large-scale data migrations
  
• Bachelor’s degree in Computer Science or related field
  

Nice to Have:

• Experience with ML data pipelines and feature engineering
  
• Exposure to streaming frameworks like Kafka
  
• Knowledge of cloud platforms like AWS, Azure, or GCP
  
• Experience with data governance tools and frameworks