About the Role
We are looking for a Software Engineer to execute large-scale data platform migrations to Snowflake and support reliable Airflow workflows.

The mandatory requirements are 3+ years of Python, advanced SQL, Snowflake modeling, Airflow, Kafka, Spark/PySpark, Iceberg, Parquet, AWS S3, testing/debugging, 2+ years with large-scale Airflow/Spark data, overlap until 12 PM Pacific Time, and upper-intermediate English. Snowflake/Airflow migrations and AI tools are a plus.

What you will do
• Work embedded within the data engineering function, partnering closely with the data platform team to support a large-scale data platform modernization effort.
• Execute the migration of approximately 1,000 datasets to Snowflake.
• Adapt existing pipelines to Snowflake, following the core architecture and technical approach defined by the internal team.
• Ensure data quality and reliability throughout the migration process.
• Support workflow scheduling and monitoring in Apache Airflow 3.
• Execute time-sensitive migrations, including Airflow 2 to 3, Confluent region migration, and the move to Iceberg.




• Help accelerate the migration initiatives targeted for completion by the end of March 2027.

Must haves
• Robust software engineering fundamentals.
• 3+ years of hands-on Python development experience.
• Advanced SQL, including complex joins, CTEs, window functions, and performance tuning.
• Snowflake data modeling.
• Apache Airflow — developing and testing pipelines in Airflow and Python.
• Apache Kafka.
• Apache Spark, including hands-on PySpark experience.
• Iceberg and Parquet data formats.
• AWS experience, particularly S3 (data lakes, partitioning, and lifecycle policies).
• Testing strategy experience, with the ability to debug and test code hands-on.
• At least 2 years of industry experience working with large-scale datasets, including Airflow and Spark.
• Overlap until 12 PM Pacific Time.
• Upper-intermediate English level.

Nice to haves
• Hands-on experience wit

📌 Software Engineer (India)
🏢 AgileEngine
📍 India