Cloud Data Engineer (Snowflake/Databricks) – Remote
Summary
Cloud Data Engineer who designs and builds scalable ETL/ELT pipelines and data platforms on Snowflake and/or Databricks, orchestrating workflows with Airflow in AWS, Azure, or GCP. Day-to-day involves SQL/Python transformation work, query performance tuning, and supporting analytics and BI teams. This is a remote position based in Poland.
- Required Skills
- Airflow
- AWS
- +19
- Remote Job
Job Description
This is a remote position.
We are seeking an experienced Cloud Data Engineer to design, build, and optimize modern data platforms using Snowflake and/or Data-bricks. This role focuses on developing scalable data pipelines, implementing reliable transformation workflows, and supporting advanced analytics across cloud environments.
You will work closely with analytics, BI, and engineering teams to ensure high-quality, performant, and secure data systems. The ideal candidate has strong SQL and Python skills and experience building production-grade data infrastructure in AWS, Azure, or GCP.
Key Responsibilities
- Design and build scalable data pipelines (ETL/ELT)
- Develop and optimize transformations in Snowflake or Data-bricks
- Improve query performance and cost efficiency
- Integrate orchestration tools (Airflow or similar)
- Support analytics and reporting teams with reliable datasets
- Ensure data quality, governance, and monitoring
- Collaborate with cross-functional teams on data initiatives
Requirements
- 4+ years of experience in Data Engineering
- Strong SQL and Python skills
- Hands-on experience with Snowflake and/or Databricks
- Experience with Spark (batch and/or streaming)
- Familiarity with orchestration tools (Airflow or similar)
- Experience working in AWS, Azure, or GCP environments
- Strong understanding of data modeling concepts
Preferred Qualifications
- Experience with dbt or similar transformation tools
- Experience with real-time data streaming (Kafka, Kinesis, Pub/Sub)
- Experience implementing data quality frameworks
- Knowledge of BI tools and downstream analytics use cases