Job Description

We are seeking a hands-on Data Engineer to support a large-scale data platform modernization initiative. You will migrate approximately 1,000 datasets to Snowflake, adapt existing pipelines, and help deliver reliable orchestration with Apache Airflow 3. The architecture and technical approach are already defined, with the role focused on implementation and migration delivery through March 2027.

Enterprise experience strongly preferred.

Key Responsibilities
Migrate pipelines from Apache Airflow 2 to Apache Airflow 3.
Migrate Confluent connections between cloud regions.
Migrate pipelines from Hive to Iceberg using Snowpark Connect.
Adapt existing data pipelines to Snowflake while maintaining data quality and reliability.
Support workflow scheduling and monitoring in Apache Airflow.
Partner with the team to execute time-sensitive data migrations.

Qualifications

Must-Have Skills
2+ years of experience.
Solid software engineering fundamentals.
Hands-on Python development experience.
Advanced SQL, including complex joins, CTEs,



window functions, and performance tuning.
Snowflake data modeling.
Apache Airflow experience developing and testing pipelines in Airflow and Python.
Apache Kafka experience.
Apache Spark experience, including hands-on PySpark.
Experience with Iceberg and Parquet data formats.
AWS experience, particularly S3 data lakes, partitioning, and lifecycle policies.
Testing strategy experience and 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.
Robust communication skills.
Ability to work independently.

Nice-to-Have Skills
Hands-on Snowflake migration experience, including data warehouse modernization and performance and cost optimization.
Apache Airflow migration experience, including version upgrades, executor changes, or platform migrations.
Experience using AI tools for development.

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