Data Engineer

Svitla Systems Inc. is looking for a Data Engineer for a full-time position (40 hours per week) in Europe. Our client is one of the world’s largest and fastest-growing job sites.

We are looking for a Data Engineer to work embedded within the data engineering function, partnering closely with the data platform team to support a large-scale data platform modernization effort. The role centers on migrating approximately 1,000 datasets to Snowflake, with Apache Airflow 3 handling orchestration. The core architecture and technical approach are already defined by the client's team, so the focus is on execution rather than design.

The overarching objective is to accelerate a set of time-sensitive migrations (Airflow 2 to 3, Confluent region migration, and the move to Iceberg), targeted for completion by the end of March 2027.

Coverage until 12:00 PM PT

Requirements

• 3+ years of industry experience working with large-scale datasets, including Airflow and Spark.
• Strong software engineering fundamentals.
• Hands-on Python development experience.
• Advanced SQL, including complex joins, CTEs, window functions, and performance tuning.
• Snowflake data modeling experience.
• Experience developing and testing pipelines in Apache Airflow and Python.
• Experience with Apache Kafka.
• Experience with Apache Spark, including hands-on PySpark.
• Experience with 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.
• Strong communication skills.
• Ability to work independently.

Will be a plus

• 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.

Responsibilities

• Carry out the migration of approximately 1,000 datasets to Snowflake, with Apache Airflow 3 handling orchestration.
• Migrate a set of pipelines from Apache Airflow 2 to Airflow 3.
• Migrate Confluent connections to a new region.
• Migrate a set of pipelines from Hive to Iceberg using Snowpark Connect.
• Adapt existing data pipelines to Snowflake while ensuring data quality and reliability throughout.
• Support workflow scheduling and monitoring in Apache Airflow.