AgileEngine

Data engineer for large-scale platforms

In short

Senior Data Engineer role to execute large-scale data platform migrations (~1,000 datasets) to Snowflake and support Apache Airflow workflows at AgileEngine, a company building software for Fortune 500 brands. The role demands strong Python, advanced SQL, Snowflake, Airflow, Kafka, Spark/PySpark, Iceberg/Parquet, and AWS S3 experience, with at least 2 years working on large-scale datasets. Remote work requires overlap until 12 PM Pacific Time and upper-intermediate English.

About the Role
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. We are looking for a Data Engineer to execute large-scale data platform migrations to Snowflake and support reliable Airflow workflows.
Responsibilities
•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.
Requirements
•Strong 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 hands-on debug and test code.
•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 Have
•Hands-on experience with Snowflake migrations (data warehouse modernization, performance and cost optimization).
•Experience with Apache Airflow migrations (version upgrades, executor changes, or platform migrations).
•Experience using AI tools for development.
Conditions
•Mentorship, TechTalks, and personalized growth roadmaps.
•USD-based pay with education, fitness, and team activity budgets.
•Modern solutions with Fortune 500 and top product companies.
•Flexible schedule with remote and office options.

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