About the position We are seeking a Senior Data Engineer with expertise in Databricks and Snowflake to join our team. This role involves designing, building, and optimizing large-scale data pipelines and data models within a hybrid work environment. The ideal candidate will have a strong background in data engineering principles, advanced SQL, and experience with data ingestion, migration, and orchestration.

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

Requirements

• 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
• 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-haves

• 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